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Studio Comparisons: at a glance

08.38 | Label:

Studio comparisons: at a glance

Using the interactive comparison tool is easy and (we hope) pretty self-explanatory. The easiest way to learn is to simply play around with the various options drag the marquee around the navigator frame.
Using the tool

The basic idea is that you can choose up to three cameras to compare to the model featured in the review, select from the available ISO and mode combinations and move the marquee around the large navigator image to view 100% crops from anywhere in the frame.
Our recommended comparison cameras are loaded by default. Pick your own from the menu above each thumbnail. Only cameras reviewed since the new studio shot was introduced are currently available (more are being added all the time). If you change the shooting mode or ISO for the master camera the nearest equivalent will automatically selected for all the comparison cameras. You can also change them independently. The text will change to reflect our findings according to the ISO range selected.
Click and drag the marquee on the main navigator window to position the 100% crops. You can also click anywhere in the frame to jump to that position. You can also click and drag any of the 100% crops - the others will move too.
The 'Show Presets' button highlights the areas of the frame used in previous reviews. Just click on them to jump to that point. JPEG and RAW (where available) modes are easily accessed.
Download links are provided for the JPEG and (zipped) raw originals. Note that not all raw files are in the system yet. Shooting information is visible by holding your cursor over the cog icon to the bottom left of each crop.
Full screen mode 

If you have a small monitor (such as a netbook) you may find that you don't have enough vertical resolution to see everything. Click on 'Open in Full Screen mode' to launch a window containing the same page in horizontal orientation. 


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Histogram

08.13 | Label:

Histogram

Histograms are the key to understanding digital images. This 10x4 mosaic contains 40 tiles which we could sort by color and then stack up accordingly. The higher the pile, the more tiles of that color in the mosaic. The resulting "histogram" would represent the color distribution of the mosaic.
In the sensor topic we learned that a digital image is basically a mosaic of square tiles or "pixels" of uniform color which are so tiny that it appears uniform and smooth. Instead of sorting them by color, we could sort these pixels into 256 levels of brightness from black (value 0) to white (value 255) with 254 gray levels in between. Just as we did manually for the mosaic, an imaging software automatically sorted the pixels of the image below into 256 groups (levels) of "brightness" and stacked them up accordingly. The height of each "stack" or vertical "bar" tells you how many pixels there are for that particular brightness. "0" and "255" are the darkest and brightest values, corresponding to black and white respectively.
On this histogram each "stack" or "bar" is one pixel wide. Unlike the mosaic histograms, the 256 bars are stacked side by side without any space between them, which is why for educational purposes, the vertical bars are shown in alternating shades of gray, allowing you to distinguish the individual bars. There are no blank spaces between bars to avoid confusion with blank spaces caused by missing tones in the image. Normally all bars will be black as indicated in the second histogram.
Typical Histogram Examples
Correctly exposed image
This is an example of a correctly exposed image with a "good" histogram. The smooth curve downwards ending in 255 shows that the subtle highlight detail in the clouds and waves is preserved. Likewise, the shadow area starts at 0 and builds up gradually.
Underexposed image
The histogram indicates there are a lot of pixels with value 0 or close to 0, which is an indication of "clipped shadows". Some shadow detail is lost forever as explained in the dynamic range topic. Unless there is a lot of pure black in the image, there should not be that many pure black pixels. There are also very few pixels in the highlight area.
Overexposed image
The histogram indicates there are a lot of pixels with value 255 or close to 255, which is an indication of "clipped highlights". Subtle highlight detail in the clouds and waves is lost. There are also very few pixels in the shadow area.
Image with too much contrast
This image has both clipped shadows and highlights. The dynamic range of the scene is larger than the dynamic range of the camera.
Image with too little contrast
This image only contains midtones and lacks contrast, resulting in a hazy image.
Image with modified contrast
When "stretching" the above histogram via a Levels or Curves adjustment, the contrast of the image improves, but since the tones are redistributed over a wider tonal range, some tones are missing, as indicated in this "combed" histogram. Too much combing can lead to posterization.
Keeping an Eye on the Histograms when Taking Pictures
Example of camera histogram review with overexposure warning
Most prosumer cameras and all professional cameras allow you to view the histogram on the camera's LCD so you can adjust the exposure and take the shot again if necessary. Some cameras come with an overexposure warning, whereby the overexposed areas blink, as indicated in this animation. Usually the blinking areas indiate that at least one of the channels is clipped.
Keeping an Eye on the Histograms when Editing
When editing images, it is important to keep an eye on the histogram to avoid the above mentioned shadow and highlight clipping and posterization. Adobe Photoshop CS and later versions come with a live histogram palette, as stated in my Photoshop CS review.
Summary
It is essential to keep an eye on the histogram when taking pictures and when editing them to ensure proper exposure and avoid losing shadow and highlight detail.

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Pixel Density

08.04 | Label:

Pixel Density

Pixel Density is a calculation of the number of pixels on a sensor, divided by the imaging area of that sensor. It can be used to understand how closely packed a sensor is and helps when comparing two cameras with different sensor sizes or numbers of photosites (pixels). Because the light collecting area and efficiency of each photosite will vary between technologies and manufacturers, pixel density should not be used as a predictor for image quality but instead as a parameter to help understand the sensor.

Diagram comparing some common sensor sizes

The APS-C sensors used in most modern DSLRs have an area of approximately 3.5 cm², while the 1/1.7" and 1/2.3" sensors commonly used in compact cameras have areas of 0.43 and 0.29 cm², respectively.
To get some idea of what this means, here is a diagram representing a pixel density of 28 MP/cm² (the pixel density of the Canon G9). As you can see, this density equates to 12 MP on the G9's 1/1.7" sensor but would be 91 MP if applied to a sensor as large as the one in a Canon 450D.
Conversely, if we look at the Canon 450D's pixel density of 3.7 MP, we can see that it gives 12 MP on a Canon APS-C sensor but would give just 1.6 MP on a 1/1.7" sensor like the one in the G9.
The calculation is based on the number of pixels produced at the camera's native resolution (Effective pixels), so both for conventional Bayer sensors and Foveon type, one photosite is considered equal to one pixel in the final image. For Fujifilm's Super CCD SR technology, each photosite contains one 's' and one 'r' photodiode but contribute only one pixel to the final image, so are classed as a single pixel.

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History Photograph

07.22 | Label:

 
    The first permanent photograph was made in 1822 by a French inventor, Joseph Nicéphore Niépce, building on a discovery by Johann Heinrich Schultz (1724): that a silver and chalk mixture darkens under exposure to light. Niépce and Louis Daguerre refined this process. Daguerre discovered that exposing the silver first to iodine vapor, before exposure to light, and then to mercury fumes after the photograph was taken, could form a latent image; bathing the plate in a salt bath then fixes the image. These ideas led to the famous daguerreotype.
  The daguerreotype had its problems, notably the fragility of the resulting picture, and that it was a positive-only process and thus could not be re-printed. Inventors set about looking for improved processes that would be more practical. Several processes were introduced and used for a short time between Niépce's first image and the introduction of the collodion process in 1848. Collodion-based wet-glass plate negatives with prints made on albumen paper remained the preferred photographic method for some time, even after the introduction of the even more practical gelatin process in 1871. Adaptations of the gelatin process have remained the primary black-and-white photographic process to this day, differing primarily in the film material itself, originally glass and then a variety of flexible films.

   Color photography is almost as old as black-and-white, with early experiments dating to John Herschel's experiments with Anthotype from 1842, and Lippmann plate from 1891. Color photography became much more popular with the introduction of Autochrome Lumière in 1903, which was replaced by Kodachrome, Ilfochrome and similar processes. For many years these processes were used almost exclusively for transparencies (in slide projectors and similar devices), but color prints became popular with the introduction of the Chromogenic negative, which is the most-used system in the C-41 process. The needs of the movie industry have also introduced a host of special-purpose systems, perhaps the best-known being the now rare Technicolor.

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