Fujifilm X-A5 Review – Test Shots

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Digital Cameras – Fujifilm X-A5 Test Images

Not sure which camera to buy? Let your eyes be the ultimate judge!
Visit our Comparometer(tm)
to compare images from the Fujifilm X-A5 with those from other
cameras you may be considering. The proof is in the pictures, so let
your own eyes decide which you like best!

Still LifeX-A5 Sample images image 1

This is our new “Still Life” test target. We’re combining
some of the elements from previous shots (DaveBox and Res Chart) into
this and the “Multi Target” shot below, plus added a number
of elements that are very revealing of various camera characteristics
and foibles.

Here’s what to look for in this target:

  • Tone-on-tone detail & noise suppression:
    The cloth swatches in the pinwheel were chosen because they show a lot
    of tone-on-tone detail, across a broad range of colors. This is just
    the sort of detail that noise suppression processing tends to flatten
    out. If you look at the detail in these swatches as the ISO increases,
    you’ll see just where different cameras start to lose subtle detail.
    — The white and tan swatches and the dark swatches tend to be particularly
    revealing of this. The label of the vinegar bottle (second from the
    right) is another great place to look for lost detail from noise suppression,
    as the image of the person at the top of the label is actually a depiction
    of a mosaic. The dark colors in the background and in the figure’s clothes
    contain detail that’s very quickly lost when a camera’s noise suppression
    system kicks in. Cameras with really high-quality, low-noise sensors
    that require little noise suppression will be able to hold onto the
    detail in these areas, many others will show only a uniform swath of
    smudged color.

    Another place where you’ll quickly see the effects of over-aggressive
    noise suppression is in the white salt grains of the salt grinder in
    lower left. Cameras are often more conservative about suppressing noise
    in highlight areas (because our eyes tend to see less of it there),
    but many cameras seem to have a hard time holding onto the subtle shadings
    that distinguish the salt grains from each other, particularly at higher
    ISO levels.

  • Fine Detail: You’ll find a lot of fine detail
    in the label of the beer bottle on the right, in its fine cursive text,
    but the other bottle labels hold a lot of fine detail as well. Fine
    text is often a good visual indicator of resolution, because our brains
    have an excellent idea of what the text should look like, so
    are very quick to notice even minor loss of detail.

    For really fine detail, look to the circular scale/calculator on the
    right side of the scene. Some of the fine lines there are extremely
    fine indeed. Looking at results from many different cameras with this
    target, we found that camera noise-suppression systems often confuse
    the fine lines with image noise, and so flatten them out. There’s also
    a nice range of fine text sizes in this chart as well, once again great
    visual cues for resolution and detail.

  • Highlight Detail: Three elements in this scene
    show off (or show up) a camera’s ability to hold onto highlight detail.
    As mentioned above, the salt grains (and reflections of the studio lights)
    in the salt mill are examples of fairly subtle highlight detail that
    cameras’ anti-noise processing sometimes obliterate. The folded white
    cloth under the mug on the right side of the frame likewise shows a
    lot of white-on-white detail that is easy to lose, particularly if a
    camera’s tone curve is too contrasty. As it turns out though, the most
    sensitive test of a camera’s highlight abilities seems to be the hank
    of white embroidery thread in the upper right corner. These fibers are
    unusually bright and reflective, so its easy for a camera to blow out
    detail in them.

  • Shadow Detail: Several elements of this subject
    are useful for evaluating shadow detail, particularly the black mug
    and the pieces of folded black velvet, both under and inside the mug.
    The bottoms of the beer bottles also provide some gradations of deep
    shadow, and the clump of peppers in the bottom of the pepper oil bottle
    had a fair bit of detail that’s far down at the shadow end of the tone
    curve.

    We were actually surprised when we constructed this scene just how dark
    the velvet and sides of the beer bottles ended up being. Even with the
    bright studio lights shining directly on it, the velvet in particular
    stays way, way down at the shadow end of the tone curve. With most cameras
    and on most monitors, the velvet will simply appear as an unrelieved
    swatch of black. To see whether it contains deep detail or not, in most
    cases you’ll have to open the file in an image editor and boost the
    brightness dramatically, to bring the detail up into a visible range.

  • Preservation of “Shape” in Strong Colors:
    As you approach the extremes of a camera’s color gamut (its range of
    recordable colors), it becomes more and more difficult for the camera
    to show fine gradations of tone, because one or more of the RGB color
    channels are close to saturation. It’s not uncommon to see a brightly
    colored piece of clothing or a vibrant flower appear in digicam photos
    as just a blob of color, because the camera ran up against the limits
    of its color gamut. The brightly colored embroidery threads in the upper
    right portion of the Still Life target are good examples of situations
    where this might happen. Pay particular attention to the bright red
    and dark blue colors here, as these are both colors near the edge of
    the typical sRGB color gamut.

  • Color accuracy and white balance: It’s pretty
    small in there, but we’ve included a mini-MacBeth chart, which displays
    very carefully controlled color swatches. Our Multi Target (see below)
    sports a full-sized MacBeth chart, but the one here serves as a good
    check of color balance and rendition, and is also useful for checking
    white balance on this particular shot.

  • Image noise and detail vs ISO: As mentioned above,
    this target contains many elements useful for evaluating detail loss
    to anti-noise processing. We’ll therefore always shoot a full set of
    test images of this target across each camera’s ISO range, for every
    camera we test. (See below.)
ISO
Series NR = Mid (Default)
100 200 400 800 1,600
3,200 6,400 12.8K 25.6K 51.2K
ISO
Series NR = Low
100 200 400 800 1,600
3,200 6,400 12.8K 25.6K 51.2K

Multi TargetX-A5 Sample images image 2

Our new “Multi Target” was first put into use in April, 2009, replacing the earlier “interim” design. This target incorporates a number of elements that combine aspects of the previous Multi target, as well as the previous Viewfinder Accuracy or “VFA” chart. Here’s some of what you’ll find in this target:

Framing marks: This chart evolved from the earlier Viewfinder Accuracy chart, so one of its major uses is to measure viewfinder accuracy. (See notes in the Viewfinder Accuracy section, at the bottom of this page, for more information on this.)

USAF resolution targets: An important use of this target is in evaluating lens quality, looking how well sharpness holds up as you move from the center to the corners of the frame. The little “USAF” resolution targets arranged at the center, in the corners, and along the diagonals are very useful for making fine judgements about blur, flare and aberrations in the image. We generally show crops of a USAF chip from a corner of the target and from the center, to show how lenses hold sharpness at wide and telephoto focal lengths.

Alignment “bullseyes:” We find these graphics from the graphic arts world (used to align sheets of film in the old film-based prepress days) very useful for seeing chromatic aberration in lenses. The bold black/white elements are good for seeing the colored fringes caused by CA in the corners of the frame.

MacBeth ColorChecker Chart: This is about as common a color standard as you can get these days, very widely available for only mildly exorbitant cost, and quite well controlled in its production. It thus serves as a good basis of comparison between cameras and between test setups. Imatest also understands the MacBeth colors very well, and uses them to produce its color accuracy map that we feature in all our reviews.

MacBeth ColorChecker SG Chart: The ColorChecker SG chart provides a wider range of colors, to give a more detailed map of a camera’s color handling. We haven’t begun using this chart in the color-accuracy graphs we routinely offer, but expect to do so at some point in the future. In the meantime, we sometimes refer to this chart internally, to get a more complete idea of what a camera’s color map looks like.

Log C/F Target: The progressive resolution pattern located just below the center of the target is a Log C/F (logarithmic contrast vs spatial frequency) chart. Digital camera noise reduction routines work by looking at levels of local contrast, flattening-out detail at progressively lower spatial frequencies as the local contrast decreases. (This is very commonly seen in human hair, grass, foliage, and other subjects with subtly-contrasting fine detail.) This chart lets Imatest analyze just how a camera makes the tradeoff between contrast, detail, and image noise.

Color Starbursts: The six circular starburst elements arranged around the target are intended to reveal de-mosaicing artifacts and color-dependent resolution issues. The six starbursts provide examples of each combination of RGB colors intersecting each other. (That is, red, green, and blue against black, plus red against green, green against blue, and blue against red.) Given that the most common sensor RGB color filter pattern (the so-called Bayer) pattern has twice as many green pixels as red or blue, you’ll generally see that the green/black starburst shows the best resolution, while the blue/red one shows the worst. The effects of different sensor geometries and color filter array patterns will be revealed here.

Musicians Image: Synthetic test patterns only tell you so much. While we have a lot of pictorial images in our other test targets, we thought it would be useful to include a small “natural” image here as well.

ISO
Series
100 200 400 800 1,600
3,200 6,400 12.8K 25.6K 51.2K

Resolution TargetX-A5 Sample images image 3

Part of the impetus in developing the new Multi Target in April 2009 was to switch to using a new 2x target for the resolution measurements, since the original ISO 12233 chart we’d used since the site first began in 1998(!) had become inadequate for testing the highest-resolution cameras. We’d for quite some time had a “homemade” 2x target, employing a shrunk version of the ISO 12233 chart, shot at 1/2 size. The resolution numbers on that chart all needed to be doubled to convert to the actual values, though, so we decided to go with a commercial 2x target to eliminate possible confusion on the part of our readers. Numbers on this new 2x resolution chart now read directly in hundreds of lines/picture height. (Because almost all of the area of this new resolution chart is now meaningful for resolution measurements, there was no longer space on it to overlay the MacBeth and other color targets on our prior Multi chart; hence the simultaneous change in our Multi target.)

“Sunlit” Portrait:
(This is our “Outdoor” Portrait test – read more about it
here.)

X-A5 Sample images image 4

The lighting in this shot is deliberately awful, about what you’d expect
from noontime sunshine here in the Atlanta, GA area. (In fact, the color
balance has been chosen to pretty well match the hazy sunshine here in
mid-August.)

The reason for the harsh lighting is to provide a real “torture
test” of how cameras handle conditions of extreme contrast; and in
particular, how well they do holding onto highlight detail.

Look for:

  • Overall color: Matching summer sunlight here in the South,
    the lighting in this scene is a bit more yellow-tinged than that in
    many parts of the country, or in the fall or winter. – So there may
    be an overall warm cast to the color. That said though, there’s a fair
    range of color represented in the bouquet, presenting a tough challenge
    for the cameras. For some reason, the blue flowers seem particularly
    hard to handle, with many cameras rendering them as purple. (In real
    life, they’re a light shade of navy blue, with just a bit of purple
    in them.)
  • Skin tones: The overall slight warm cast will tend to leave
    the model’s skin tones a bit on the warm side as well. Nonetheless,
    look to see if her skin seems overly pink or if they have a too-bright
    tinge of yellow: Some cameras oversaturate skin tones (make their color
    too intense), leading to an almost sunburned look. A little oversaturation
    can make for a more “healthy-looking” complexion, but it doesn’t
    take much variation for skin tones to look unnatural.
  • Highlight detail: When the model’s skin tones are at a more
    or less normal level of brightness, how much detail can you see in her
    shirt? Does it blow out entirely to white, or can you still see the
    creases and folds in the fabric?
  • Overall contrast: Most consumer digital cameras produce bright,
    contrasty images, because that’s what most consumers like. Unfortunately,
    under bright sunlit conditions, many such cameras produce images with
    little or no highlight detail, and dark, plugged-up looking shadows.
  • Shadow detail: The area under the flower bouquet is in quite deep shadow. Does the camera in question retain good detail here, with low image noise? To see, you may need to download the image and play with it in Photoshop(tm) or another imaging program. Brighten the image, and see how far detail extends into the shadows. Photo printers are generally much better at showing shadow detail than are CRTs or LCDs, so you’ll want a camera that preserves good detail here. The ability to boost brightness without encountering too much image noise is important if you ever have to “rescue” an underexposed image on the computer.
  • Detail in areas of subtle contrast: Most digital cameras employ
    some sort of noise-suppression to remove electronic noise from their
    images. Noise suppression is a good thing, but only if it’s not overdone.
    Too much noise suppression will “flatten out” subtle detail
    in areas of reduced contrast. You can often see this in hair, where
    the individual strands become blurred, and the image takes on an almost
    watercolor effect. Look at the detail in the model’s hair, and compare
    how it looks with different cameras in the Comparometer.

To view the entire exposure series from zero to +1.0 EV, see files XA5OUTAP0.HTM through XA5OUTBAP3.HTM on the thumbnail
index page
.

Highlight Tone Series
-2
X-A5 Sample images image 5
-1
X-A5 Sample images image 6
0
X-A5 Sample images image 7
+1
X-A5 Sample images image 8
+2
X-A5 Sample images image 9
Shadow Tone Series
-2
X-A5 Sample images image 10
-1
X-A5 Sample images image 11
0
X-A5 Sample images image 12
+1
X-A5 Sample images image 13
+2
X-A5 Sample images image 14
D-Range
Series
DR100
X-A5 Sample images image 15
DR200
X-A5 Sample images image 16
DR400
X-A5 Sample images image 17

Indoor Portrait, No Flash:

Auto White Balance
X-A5 Sample images image 18
Incandescent WB
X-A5 Sample images image 19
Manual WB
X-A5 Sample images image 20

The incandescent lighting used in most US homes actually has a very
strong yellow color to it. Our eyes have an amazing ability to ignore
color casts like this, something digital cameras struggle to emulate.

The incandescent lighting used for this shot is thus not only very common
here in the US, but also very difficult for most digital cameras to deal
with. While we probably want a little yellow color to remain in
the image (to convey some of the mood of the original scene), too much
will look unnatural and distort colors.

Most cameras’ auto white balance systems have a great deal of difficulty
with this shot, but many incandescent white balance settings struggle
as well. (It seems that many cameras’ incandescent settings are actually
calibrated to the tungsten lighting used in professional studio systems,
which isn’t nearly as warm-toned as typical household lighting.)

If you intend to do much shooting indoors after dark, pay careful attention
to this test, as cameras vary widely in this regard.

To view the entire exposure series from zero to +1.0 EV, see files XA5INBMP0.HTM
through XA5INBMP3.HTM on the thumbnail index
page
.

ISO Series:
“ISO equivalent” refers to a camera’s light sensitivity. ISO
200 represents twice the sensitivity of ISO 100, meaning that you can
use a shutter speed that’s twice as fast. Higher ISO settings are often
required to get any picture at all when shooting after dark, but even
in full daylight, using a higher ISO can help you freeze fast action.
The problem is, increasing a digital camera’s ISO also increases image
noise. In practical terms, this means that higher-ISO images often can’t
be used to produce prints as large as lower-ISO ones. The tricky thing
here is that high-ISO images often look much different when printed at
various sizes than they do when viewed on-screen. In particular, for any
level of image noise, you’ll often find that while noise is quite evident
at larger print sizes, as you reduce the size of the prints, there will
come a point where it suddenly ceases to be an issue. We routinely print
high-ISO photos from the cameras we test on our studio printer (currently
a Canon i9900) at a range of sizes, and report our findings. If you’re
interested in investigating the effect of image noise for yourself, don’t
judge cameras’ performance by how their images look on your CRT, viewed
pixel-for-pixel. Rather, download the test shots linked in the table below
and output them on your own printer, so you can see how prints of various
sizes will actually look.

One additional note about this particular test series though: Because
these images are shot under household incandescent lighting, the camera
has to boost its blue-channel signal quite a bit to get back to a neutral
color balance. Since the blue channel is generally the one with the most
noise, this makes this shot a real acid test of noise performance. Noise
levels in high-ISO shots taken under daylight conditions usually won’t
show as much noise. (See the “Far Field” test for examples of
high ISO shots captured in daylight.)

ISO
Series
100 200 400 800 1,600
3,200 6,400 12.8K 25.6K 51.2K

Indoor Portrait, Flash

Normal Flash
+0.7 EV
X-A5 Sample images image 21

This shot duplicates indoor shooting conditions in most US homes, with fairly bright incandescent room lighting. The challenge here is for the camera’s flash to blend naturally with the room lighting, and produce good, neutral color overall. – Some cameras will be overly affected by the room lighting, even with their flash enabled, and the result will be a strong orange cast. Another common failing is for the highlights from the flash to take on an unnatural bluish cast.

Finally, exposure is important here, and frequently a tough challenge for the cameras. The model’s white shirt is central in the scene, reflecting a lot of the light from the flash right back at the camera. As a result, most cameras underexpose this shot, and require some positive exposure compensation to produce a good result. – And that’s an important consideration in itself: Does the camera even permit adjustment of its flash exposures? Many do not. These photos are a tough exposure challenge, if they come out OK, the camera in question can probably be coaxed into delivering a good flash exposure of any subject within its range.

Note too, that cameras may need to boost ISO to achieve a bright exposure, especially if it has a weak flash. That makes this shot a good one to look for the effect of over-aggressive noise suppression in the model’s hair.

To view the exposure series from zero to +1.0 EV in the normal flash mode with Auto ISO, see files XA5INBFAP0.HTM through XA5INBFAP3.HTM on the thumbnail index page.

Viewfinder Accuracy

Viewfinder accuracy is an important parameter, especially for shots
where framing is critical. The optical viewfinders on most digital cameras
match the (poor) accuracy of those on film cameras, typically showing
only about 85% of the actual final frame area. It’s likely that this is
a deliberate design choice by the camera engineers, to help avoid users
accidentally cutting off the heads of their subjects. We disagree with
this approach, or at least feel that it should be mitigated a bit, perhaps
by increasing the accuracy to 90 to 95%.

Unlike the optical viewfinders, the LCD viewfinders on most digital
cameras tend to be quite accurate. There are exceptions though, and it’s
unfortunately not uncommon to find an LCD monitor that only shows 90%
or less of the final frame.

Things to look for on this test chart are:

  • Optical/Electronic viewfinder accuracy: When we shoot this target in the studio, we line things up so the center of the bright red outline on the target is just visible at the edges of the viewfinder frame. The resulting photo then very directly shows how accurate the viewfinder is. The fine black lines mark progressive increments of 1% of increased or decreased frame area. The bold black lines mark 5% increments. The lines let you get an approximate idea of frame accuracy visually, but we measure the actual pixel dimensions to derive the accuracy numbers we report in our reviews.
  • LCD monitor accuracy: This is the same test, but framed with the LCD monitor instead of the optical viewfinder. As mentioned above, LCD monitors are usually more accurate than optical viewfinders, especially in point & shoot digicams.

X-A5 Sample images image 22
LCD Monitor

Digital Cameras – Fujifilm X-A5 Test Images

Not sure which camera to buy? Let your eyes be the ultimate judge!
Visit our Comparometer(tm)
to compare images from the Fujifilm X-A5 with those from other
cameras you may be considering. The proof is in the pictures, so let
your own eyes decide which you like best!

Still LifeX-A5 Test Shots image 1

This is our new “Still Life” test target. We’re combining
some of the elements from previous shots (DaveBox and Res Chart) into
this and the “Multi Target” shot below, plus added a number
of elements that are very revealing of various camera characteristics
and foibles.

Here’s what to look for in this target:

  • Tone-on-tone detail & noise suppression:
    The cloth swatches in the pinwheel were chosen because they show a lot
    of tone-on-tone detail, across a broad range of colors. This is just
    the sort of detail that noise suppression processing tends to flatten
    out. If you look at the detail in these swatches as the ISO increases,
    you’ll see just where different cameras start to lose subtle detail.
    — The white and tan swatches and the dark swatches tend to be particularly
    revealing of this. The label of the vinegar bottle (second from the
    right) is another great place to look for lost detail from noise suppression,
    as the image of the person at the top of the label is actually a depiction
    of a mosaic. The dark colors in the background and in the figure’s clothes
    contain detail that’s very quickly lost when a camera’s noise suppression
    system kicks in. Cameras with really high-quality, low-noise sensors
    that require little noise suppression will be able to hold onto the
    detail in these areas, many others will show only a uniform swath of
    smudged color.

    Another place where you’ll quickly see the effects of over-aggressive
    noise suppression is in the white salt grains of the salt grinder in
    lower left. Cameras are often more conservative about suppressing noise
    in highlight areas (because our eyes tend to see less of it there),
    but many cameras seem to have a hard time holding onto the subtle shadings
    that distinguish the salt grains from each other, particularly at higher
    ISO levels.

  • Fine Detail: You’ll find a lot of fine detail
    in the label of the beer bottle on the right, in its fine cursive text,
    but the other bottle labels hold a lot of fine detail as well. Fine
    text is often a good visual indicator of resolution, because our brains
    have an excellent idea of what the text should look like, so
    are very quick to notice even minor loss of detail.

    For really fine detail, look to the circular scale/calculator on the
    right side of the scene. Some of the fine lines there are extremely
    fine indeed. Looking at results from many different cameras with this
    target, we found that camera noise-suppression systems often confuse
    the fine lines with image noise, and so flatten them out. There’s also
    a nice range of fine text sizes in this chart as well, once again great
    visual cues for resolution and detail.

  • Highlight Detail: Three elements in this scene
    show off (or show up) a camera’s ability to hold onto highlight detail.
    As mentioned above, the salt grains (and reflections of the studio lights)
    in the salt mill are examples of fairly subtle highlight detail that
    cameras’ anti-noise processing sometimes obliterate. The folded white
    cloth under the mug on the right side of the frame likewise shows a
    lot of white-on-white detail that is easy to lose, particularly if a
    camera’s tone curve is too contrasty. As it turns out though, the most
    sensitive test of a camera’s highlight abilities seems to be the hank
    of white embroidery thread in the upper right corner. These fibers are
    unusually bright and reflective, so its easy for a camera to blow out
    detail in them.

  • Shadow Detail: Several elements of this subject
    are useful for evaluating shadow detail, particularly the black mug
    and the pieces of folded black velvet, both under and inside the mug.
    The bottoms of the beer bottles also provide some gradations of deep
    shadow, and the clump of peppers in the bottom of the pepper oil bottle
    had a fair bit of detail that’s far down at the shadow end of the tone
    curve.

    We were actually surprised when we constructed this scene just how dark
    the velvet and sides of the beer bottles ended up being. Even with the
    bright studio lights shining directly on it, the velvet in particular
    stays way, way down at the shadow end of the tone curve. With most cameras
    and on most monitors, the velvet will simply appear as an unrelieved
    swatch of black. To see whether it contains deep detail or not, in most
    cases you’ll have to open the file in an image editor and boost the
    brightness dramatically, to bring the detail up into a visible range.

  • Preservation of “Shape” in Strong Colors:
    As you approach the extremes of a camera’s color gamut (its range of
    recordable colors), it becomes more and more difficult for the camera
    to show fine gradations of tone, because one or more of the RGB color
    channels are close to saturation. It’s not uncommon to see a brightly
    colored piece of clothing or a vibrant flower appear in digicam photos
    as just a blob of color, because the camera ran up against the limits
    of its color gamut. The brightly colored embroidery threads in the upper
    right portion of the Still Life target are good examples of situations
    where this might happen. Pay particular attention to the bright red
    and dark blue colors here, as these are both colors near the edge of
    the typical sRGB color gamut.

  • Color accuracy and white balance: It’s pretty
    small in there, but we’ve included a mini-MacBeth chart, which displays
    very carefully controlled color swatches. Our Multi Target (see below)
    sports a full-sized MacBeth chart, but the one here serves as a good
    check of color balance and rendition, and is also useful for checking
    white balance on this particular shot.

  • Image noise and detail vs ISO: As mentioned above,
    this target contains many elements useful for evaluating detail loss
    to anti-noise processing. We’ll therefore always shoot a full set of
    test images of this target across each camera’s ISO range, for every
    camera we test. (See below.)
ISO
Series NR = Mid (Default)
100 200 400 800 1,600
3,200 6,400 12.8K 25.6K 51.2K
ISO
Series NR = Low
100 200 400 800 1,600
3,200 6,400 12.8K 25.6K 51.2K

Multi TargetX-A5 Test Shots image 2

Our new “Multi Target” was first put into use in April, 2009, replacing the earlier “interim” design. This target incorporates a number of elements that combine aspects of the previous Multi target, as well as the previous Viewfinder Accuracy or “VFA” chart. Here’s some of what you’ll find in this target:

Framing marks: This chart evolved from the earlier Viewfinder Accuracy chart, so one of its major uses is to measure viewfinder accuracy. (See notes in the Viewfinder Accuracy section, at the bottom of this page, for more information on this.)

USAF resolution targets: An important use of this target is in evaluating lens quality, looking how well sharpness holds up as you move from the center to the corners of the frame. The little “USAF” resolution targets arranged at the center, in the corners, and along the diagonals are very useful for making fine judgements about blur, flare and aberrations in the image. We generally show crops of a USAF chip from a corner of the target and from the center, to show how lenses hold sharpness at wide and telephoto focal lengths.

Alignment “bullseyes:” We find these graphics from the graphic arts world (used to align sheets of film in the old film-based prepress days) very useful for seeing chromatic aberration in lenses. The bold black/white elements are good for seeing the colored fringes caused by CA in the corners of the frame.

MacBeth ColorChecker Chart: This is about as common a color standard as you can get these days, very widely available for only mildly exorbitant cost, and quite well controlled in its production. It thus serves as a good basis of comparison between cameras and between test setups. Imatest also understands the MacBeth colors very well, and uses them to produce its color accuracy map that we feature in all our reviews.

MacBeth ColorChecker SG Chart: The ColorChecker SG chart provides a wider range of colors, to give a more detailed map of a camera’s color handling. We haven’t begun using this chart in the color-accuracy graphs we routinely offer, but expect to do so at some point in the future. In the meantime, we sometimes refer to this chart internally, to get a more complete idea of what a camera’s color map looks like.

Log C/F Target: The progressive resolution pattern located just below the center of the target is a Log C/F (logarithmic contrast vs spatial frequency) chart. Digital camera noise reduction routines work by looking at levels of local contrast, flattening-out detail at progressively lower spatial frequencies as the local contrast decreases. (This is very commonly seen in human hair, grass, foliage, and other subjects with subtly-contrasting fine detail.) This chart lets Imatest analyze just how a camera makes the tradeoff between contrast, detail, and image noise.

Color Starbursts: The six circular starburst elements arranged around the target are intended to reveal de-mosaicing artifacts and color-dependent resolution issues. The six starbursts provide examples of each combination of RGB colors intersecting each other. (That is, red, green, and blue against black, plus red against green, green against blue, and blue against red.) Given that the most common sensor RGB color filter pattern (the so-called Bayer) pattern has twice as many green pixels as red or blue, you’ll generally see that the green/black starburst shows the best resolution, while the blue/red one shows the worst. The effects of different sensor geometries and color filter array patterns will be revealed here.

Musicians Image: Synthetic test patterns only tell you so much. While we have a lot of pictorial images in our other test targets, we thought it would be useful to include a small “natural” image here as well.

ISO
Series
100 200 400 800 1,600
3,200 6,400 12.8K 25.6K 51.2K

Resolution TargetX-A5 Test Shots image 3

Part of the impetus in developing the new Multi Target in April 2009 was to switch to using a new 2x target for the resolution measurements, since the original ISO 12233 chart we’d used since the site first began in 1998(!) had become inadequate for testing the highest-resolution cameras. We’d for quite some time had a “homemade” 2x target, employing a shrunk version of the ISO 12233 chart, shot at 1/2 size. The resolution numbers on that chart all needed to be doubled to convert to the actual values, though, so we decided to go with a commercial 2x target to eliminate possible confusion on the part of our readers. Numbers on this new 2x resolution chart now read directly in hundreds of lines/picture height. (Because almost all of the area of this new resolution chart is now meaningful for resolution measurements, there was no longer space on it to overlay the MacBeth and other color targets on our prior Multi chart; hence the simultaneous change in our Multi target.)

“Sunlit” Portrait:
(This is our “Outdoor” Portrait test – read more about it
here.)

X-A5 Test Shots image 4

The lighting in this shot is deliberately awful, about what you’d expect
from noontime sunshine here in the Atlanta, GA area. (In fact, the color
balance has been chosen to pretty well match the hazy sunshine here in
mid-August.)

The reason for the harsh lighting is to provide a real “torture
test” of how cameras handle conditions of extreme contrast; and in
particular, how well they do holding onto highlight detail.

Look for:

  • Overall color: Matching summer sunlight here in the South,
    the lighting in this scene is a bit more yellow-tinged than that in
    many parts of the country, or in the fall or winter. – So there may
    be an overall warm cast to the color. That said though, there’s a fair
    range of color represented in the bouquet, presenting a tough challenge
    for the cameras. For some reason, the blue flowers seem particularly
    hard to handle, with many cameras rendering them as purple. (In real
    life, they’re a light shade of navy blue, with just a bit of purple
    in them.)
  • Skin tones: The overall slight warm cast will tend to leave
    the model’s skin tones a bit on the warm side as well. Nonetheless,
    look to see if her skin seems overly pink or if they have a too-bright
    tinge of yellow: Some cameras oversaturate skin tones (make their color
    too intense), leading to an almost sunburned look. A little oversaturation
    can make for a more “healthy-looking” complexion, but it doesn’t
    take much variation for skin tones to look unnatural.
  • Highlight detail: When the model’s skin tones are at a more
    or less normal level of brightness, how much detail can you see in her
    shirt? Does it blow out entirely to white, or can you still see the
    creases and folds in the fabric?
  • Overall contrast: Most consumer digital cameras produce bright,
    contrasty images, because that’s what most consumers like. Unfortunately,
    under bright sunlit conditions, many such cameras produce images with
    little or no highlight detail, and dark, plugged-up looking shadows.
  • Shadow detail: The area under the flower bouquet is in quite deep shadow. Does the camera in question retain good detail here, with low image noise? To see, you may need to download the image and play with it in Photoshop(tm) or another imaging program. Brighten the image, and see how far detail extends into the shadows. Photo printers are generally much better at showing shadow detail than are CRTs or LCDs, so you’ll want a camera that preserves good detail here. The ability to boost brightness without encountering too much image noise is important if you ever have to “rescue” an underexposed image on the computer.
  • Detail in areas of subtle contrast: Most digital cameras employ
    some sort of noise-suppression to remove electronic noise from their
    images. Noise suppression is a good thing, but only if it’s not overdone.
    Too much noise suppression will “flatten out” subtle detail
    in areas of reduced contrast. You can often see this in hair, where
    the individual strands become blurred, and the image takes on an almost
    watercolor effect. Look at the detail in the model’s hair, and compare
    how it looks with different cameras in the Comparometer.

To view the entire exposure series from zero to +1.0 EV, see files XA5OUTAP0.HTM through XA5OUTBAP3.HTM on the thumbnail
index page
.

Highlight Tone Series
-2
X-A5 Test Shots image 5
-1
X-A5 Test Shots image 6
0
X-A5 Test Shots image 7
+1
X-A5 Test Shots image 8
+2
X-A5 Test Shots image 9
Shadow Tone Series
-2
X-A5 Test Shots image 10
-1
X-A5 Test Shots image 11
0
X-A5 Test Shots image 12
+1
X-A5 Test Shots image 13
+2
X-A5 Test Shots image 14
D-Range
Series
DR100
X-A5 Test Shots image 15
DR200
X-A5 Test Shots image 16
DR400
X-A5 Test Shots image 17

Indoor Portrait, No Flash:

Auto White Balance
X-A5 Test Shots image 18
Incandescent WB
X-A5 Test Shots image 19
Manual WB
X-A5 Test Shots image 20

The incandescent lighting used in most US homes actually has a very
strong yellow color to it. Our eyes have an amazing ability to ignore
color casts like this, something digital cameras struggle to emulate.

The incandescent lighting used for this shot is thus not only very common
here in the US, but also very difficult for most digital cameras to deal
with. While we probably want a little yellow color to remain in
the image (to convey some of the mood of the original scene), too much
will look unnatural and distort colors.

Most cameras’ auto white balance systems have a great deal of difficulty
with this shot, but many incandescent white balance settings struggle
as well. (It seems that many cameras’ incandescent settings are actually
calibrated to the tungsten lighting used in professional studio systems,
which isn’t nearly as warm-toned as typical household lighting.)

If you intend to do much shooting indoors after dark, pay careful attention
to this test, as cameras vary widely in this regard.

To view the entire exposure series from zero to +1.0 EV, see files XA5INBMP0.HTM
through XA5INBMP3.HTM on the thumbnail index
page
.

ISO Series:
“ISO equivalent” refers to a camera’s light sensitivity. ISO
200 represents twice the sensitivity of ISO 100, meaning that you can
use a shutter speed that’s twice as fast. Higher ISO settings are often
required to get any picture at all when shooting after dark, but even
in full daylight, using a higher ISO can help you freeze fast action.
The problem is, increasing a digital camera’s ISO also increases image
noise. In practical terms, this means that higher-ISO images often can’t
be used to produce prints as large as lower-ISO ones. The tricky thing
here is that high-ISO images often look much different when printed at
various sizes than they do when viewed on-screen. In particular, for any
level of image noise, you’ll often find that while noise is quite evident
at larger print sizes, as you reduce the size of the prints, there will
come a point where it suddenly ceases to be an issue. We routinely print
high-ISO photos from the cameras we test on our studio printer (currently
a Canon i9900) at a range of sizes, and report our findings. If you’re
interested in investigating the effect of image noise for yourself, don’t
judge cameras’ performance by how their images look on your CRT, viewed
pixel-for-pixel. Rather, download the test shots linked in the table below
and output them on your own printer, so you can see how prints of various
sizes will actually look.

One additional note about this particular test series though: Because
these images are shot under household incandescent lighting, the camera
has to boost its blue-channel signal quite a bit to get back to a neutral
color balance. Since the blue channel is generally the one with the most
noise, this makes this shot a real acid test of noise performance. Noise
levels in high-ISO shots taken under daylight conditions usually won’t
show as much noise. (See the “Far Field” test for examples of
high ISO shots captured in daylight.)

ISO
Series
100 200 400 800 1,600
3,200 6,400 12.8K 25.6K 51.2K

Indoor Portrait, Flash

Normal Flash
+0.7 EV
X-A5 Test Shots image 21

This shot duplicates indoor shooting conditions in most US homes, with fairly bright incandescent room lighting. The challenge here is for the camera’s flash to blend naturally with the room lighting, and produce good, neutral color overall. – Some cameras will be overly affected by the room lighting, even with their flash enabled, and the result will be a strong orange cast. Another common failing is for the highlights from the flash to take on an unnatural bluish cast.

Finally, exposure is important here, and frequently a tough challenge for the cameras. The model’s white shirt is central in the scene, reflecting a lot of the light from the flash right back at the camera. As a result, most cameras underexpose this shot, and require some positive exposure compensation to produce a good result. – And that’s an important consideration in itself: Does the camera even permit adjustment of its flash exposures? Many do not. These photos are a tough exposure challenge, if they come out OK, the camera in question can probably be coaxed into delivering a good flash exposure of any subject within its range.

Note too, that cameras may need to boost ISO to achieve a bright exposure, especially if it has a weak flash. That makes this shot a good one to look for the effect of over-aggressive noise suppression in the model’s hair.

To view the exposure series from zero to +1.0 EV in the normal flash mode with Auto ISO, see files XA5INBFAP0.HTM through XA5INBFAP3.HTM on the thumbnail index page.

Viewfinder Accuracy

Viewfinder accuracy is an important parameter, especially for shots
where framing is critical. The optical viewfinders on most digital cameras
match the (poor) accuracy of those on film cameras, typically showing
only about 85% of the actual final frame area. It’s likely that this is
a deliberate design choice by the camera engineers, to help avoid users
accidentally cutting off the heads of their subjects. We disagree with
this approach, or at least feel that it should be mitigated a bit, perhaps
by increasing the accuracy to 90 to 95%.

Unlike the optical viewfinders, the LCD viewfinders on most digital
cameras tend to be quite accurate. There are exceptions though, and it’s
unfortunately not uncommon to find an LCD monitor that only shows 90%
or less of the final frame.

Things to look for on this test chart are:

  • Optical/Electronic viewfinder accuracy: When we shoot this target in the studio, we line things up so the center of the bright red outline on the target is just visible at the edges of the viewfinder frame. The resulting photo then very directly shows how accurate the viewfinder is. The fine black lines mark progressive increments of 1% of increased or decreased frame area. The bold black lines mark 5% increments. The lines let you get an approximate idea of frame accuracy visually, but we measure the actual pixel dimensions to derive the accuracy numbers we report in our reviews.
  • LCD monitor accuracy: This is the same test, but framed with the LCD monitor instead of the optical viewfinder. As mentioned above, LCD monitors are usually more accurate than optical viewfinders, especially in point & shoot digicams.

X-A5 Test Shots image 22
LCD Monitor

All test shots

Fujifilm X-A5 Thumbnails

Not sure which camera to buy? Let your eyes be the ultimate judge!
Visit our Comparometer(tm)
to compare images from the Fujifilm X-A5 with those from other
cameras you may be considering. The proof is in the pictures, so let
your own eyes decide which you like best!

This page may take a long time to load, due to the many thumbnails!

All images copyright © 2017 by The Imaging Resource. All rights reserved.

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XA5OUTB_HDR3.JPG
6,633,222 bytes
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f8.0
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90.0 mm focal length
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XA5OUTB_HDRA.JPG
6,359,263 bytes
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1/75 sec
f8.0
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90.0 mm focal length
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XA5OUTB_HDR_ART.JPG
7,919,680 bytes
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1/150 sec
f5.6
0.0 EV
90.0 mm focal length
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XA5hRES.JPG
XA5hRES.RAF
6,694,422 bytes
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f5.6
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90.0 mm focal length
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XA5hRES_ACRu300r05.JPG
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f5.6
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90.0 mm focal length
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XA5hSLI00100NR1.JPG
11,081,370 bytes
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90.0 mm focal length
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XA5hSLI00100NR3D.JPG
10,727,000 bytes
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XA5hSLI00200NR1.JPG
XA5hSLI00200NR1.RAF
10,114,843 bytes
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f8.0
0.0 EV
90.0 mm focal length
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XA5hSLI00200NR3D.JPG
XA5hSLI00200NR3D.RAF
9,696,567 bytes
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90.0 mm focal length
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XA5hSLI00200_ACR.JPG
15,228,589 bytes
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0.0 EV
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XA5hSLI00200_ACRu400r03.JPG
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90.0 mm focal length
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XA5hSLI00400NR1.JPG
XA5hSLI00400NR1.RAF
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1/25 sec
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XA5hSLI00400NR3D.JPG
XA5hSLI00400NR3D.RAF
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1/25 sec
f8.0
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XA5hSLI00400_ACR.JPG
16,717,626 bytes
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XA5hSLI00800NR1.JPG
XA5hSLI00800NR1.RAF
10,393,291 bytes
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XA5hSLI00800NR3D.JPG
XA5hSLI00800NR3D.RAF
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XA5hSLI00800_ACR.JPG
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90.0 mm focal length
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XA5hSLI01600NR1.JPG
XA5hSLI01600NR1.RAF
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f8.0
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XA5hSLI01600NR3D.JPG
XA5hSLI01600NR3D.RAF
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f8.0
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XA5hSLI01600_ACR.JPG
21,670,483 bytes
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f8.0
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XA5hSLI03200NR1.JPG
XA5hSLI03200NR1.RAF
9,958,693 bytes
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1/200 sec
f8.0
0.0 EV
90.0 mm focal length
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XA5hSLI03200NR3D.JPG
XA5hSLI03200NR3D.RAF
9,394,051 bytes
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f8.0
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XA5hSLI03200_ACR.JPG
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1/200 sec
f8.0
0.0 EV
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XA5hSLI06400NR1.JPG
XA5hSLI06400NR1.RAF
10,252,376 bytes
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1/400 sec
f8.0
0.0 EV
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XA5hSLI06400NR3D.JPG
XA5hSLI06400NR3D.RAF
9,728,049 bytes
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f8.0
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XA5hSLI06400_ACR.JPG
29,424,607 bytes
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f8.0
0.0 EV
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XA5hSLI12800NR1.JPG
XA5hSLI12800NR1.RAF
11,332,277 bytes
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1/800 sec
f8.0
0.0 EV
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XA5hSLI12800NR3D.JPG
XA5hSLI12800NR3D.RAF
10,689,181 bytes
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f8.0
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XA5hSLI12800_ACR.JPG
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f8.0
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XA5hSLI25600NR1.JPG
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f8.0
0.0 EV
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XA5hSLI25600NR3D.JPG
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XA5hSLI51200NR1.JPG
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f8.0
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XA5hSLI51200NR3D.JPG
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f8.0
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XA5hVFAI00100.JPG
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f5.6
0.0 EV
90.0 mm focal length
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XA5hVFAI00200.JPG
XA5hVFAI00200.RAF
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6000×4000
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f5.6
0.0 EV
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XA5hVFAI00400.JPG
XA5hVFAI00400.RAF
8,361,717 bytes
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f5.6
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XA5hVFAI00800.JPG
XA5hVFAI00800.RAF
8,552,029 bytes
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f5.6
0.0 EV
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XA5hVFAI01600.JPG
XA5hVFAI01600.RAF
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f5.6
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XA5hVFAI03200.JPG
XA5hVFAI03200.RAF
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f5.6
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XA5hVFAI06400.JPG
XA5hVFAI06400.RAF
9,568,390 bytes
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1/1000 sec
f5.6
0.0 EV
90.0 mm focal length
ISO 6400
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XA5hVFAI12800.JPG
XA5hVFAI12800.RAF
10,784,166 bytes
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1/2000 sec
f5.6
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ISO 12800
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XA5hVFAI25600.JPG
11,477,492 bytes
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1/4000 sec
f5.6
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90.0 mm focal length
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XA5hVFAI51200.JPG
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1/4000 sec
f8.0
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XA5hVFAL.JPG
XA5hVFAL.RAF
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f5.6
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XA5hVFA_ADOBE.JPG
XA5hVFA_ADOBE.RAF
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6000×4000
1/40 sec
f5.6
0.0 EV
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ISO 200
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