Want to see how far DSLRs have come in the past decade? Lee Morris of Fstoppers published these two photos taken at Super Bowl halftime shows. The crop on the left was captured in 2001, possibly with the Nikon D1H at 2.7 megapixels and ISO 800 (state of the art specs at the time). The slice on the right was from this past weekend, and was shot with a Nikon D3s at 12MP and ISO 12,800.

Image credits: Photographs by Lonny Krasnow/AP and FilmMagic

When Fujifilm said that the X-Pro1′s sensor “resolution and low noise will surpass rival 35mm full size sensor[s]“, they weren’t kidding. Photographers Christian Fletcher and Michael Coyne have both been testing out the camera, and have extremely positive things to say about it:

My initial feelings are that this camera is a worthy replacement for a bulky dslr system. If you have to travel light, this is the camera for you. Physically it is only marginally larger than the x100 so slinging it around your neck for a day is no problem. In fact I am wearing mine right now!, it is a fashion accessory!! Man bling! or Girl Bling too for that matter. [#]

Fletcher has published a number of untouched sample photos to his blog, including the ISO 6400 image above shot by Coyne. Click here to check out the full-res version (be prepared to pick your jaw up off the floor). Some more sample photos can be seen here, including an ISO 25600 one.

First images from the Fujifilm X-Pro1 (via Photo Rumors)

In other news, Fujifilm has revealed that it has sold roughly 100,000 X100 cameras through 2011.

Image credit: Photograph by Michael Coyne

Technicolor just released a new Picture Profile for Canon DSLRs, and recommended that ISO be used in multiples of 160. Andrew Schär decided to test this using his Canon 60D, and found that in terms of the amount of noise present in the footage, ISO numbers that are multiples of 160 are best (i.e. least noise), followed by multiples of 100, and finally multiples of 125 being worst.
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When learning about ISO, you’ve probably heard that the lower the number, the lower the noise and the higher the image quality, but did you know that this isn’t always the case? The reason is something called the base (or native) ISO of a camera — the ISO achieved without amplifying the data from the sensor. This is usually somewhere between ISO 100 and ISO 200. Why does this matter? Bob Andersson of Camera Labs explains:

We all know that using high ISO numbers results in more sensor noise. More surprising, perhaps, is that using an ISO number below the native ISO number also degrades the image.

An interesting example is that when shooting on a Canon EOS 1Ds MkII, ISO 50 has roughly the same signal to noise ratio as shooting at ISO 800. This explains why the lowest possible ISO numbers can only be accessed through custom functions on some cameras.

Know your Base (or Native) ISO (via Reddit)

Image credit: Photograph by Filya1

Nikon will reportedly announce the new D5100 DSLR tomorrow (late tonight for those in the US), and photographs of the camera were leaked onto the Interwebs today. We’ll be reporting on the specs tomorrow, but an interesting rumor is that the camera will have a “Night Vision” option that boosts ISO up to a mind-blowing 102400, allowing you to shoot in near-darkness. Stay tuned for the official announcement!

(via Nikon Rumors)

Last Friday an anonymous poster on the photography board of 4chan sparked a discussion that rippled into the blogosphere after freezing their camera to see whether ISO performance improves at lower temperatures.

They stuck their Sony A350 into the freezer for 15 minutes, and posted the following before and after comparison of noise at ISO 3200:

Regardless of whether or not these results were fabricated, it has long been (though perhaps not widely) known among photographers that digital cameras have better ISO performance (i.e. less noise) at lower temperatures, which is why sensors are often cooled for astro-photography. Other photographers also report improved ISO performance when shooting in very cold environments.

Zodiac Light did an interesting experiment in which a Canon 350D was cooled, and the amount of noise measured. They found that cooling the sensor resulted in a 40% drop in the amount of noise.

Obviously you shouldn’t freeze your nice camera to test this out yourself, but it’s an interesting fact to know, and could be useful if you’re interested in long exposure photography.

(via The Phoblographer)

Thanks to Nathan Yan for briefing us on thermal noise.

Image credit: Don’t drop your camera! by Island-Life and used with permission.

Something you may have noticed when adjusting your camera’s ISO setting is that as you increase ISO, the number of remaining shots you have decreases. This is because the size of each photograph increases with ISO, and thus less of them can be stored in the available space of your memory card.

So why does the file size increase as you increase ISO? The answer has to do with image noise and file compression. First we’ll discuss the noise element.

Image Noise

You probably know already that a higher ISO number leads to more noise in the resulting image. This is because digital cameras achieve the same behavior of “more sensitive film” by amplifying the image signal the camera receives when it captures a photograph. This amplification also amplifies the noise that exists in every image regardless of ISO, and therefore higher ISOs have highly amplified noise.

To demonstrate, I captured the following photograph at both ISO 100 and ISO 3200:

Here’s a side by side comparison of crops from the two images:

The noise should be pretty obvious. The RAW file of the ISO100 version is 10.2MB in size, while the ISO3200 version is 14.7MB. In this case, the higher ISO leads to a 44% larger file.

An interesting property of digital cameras is that there is more noise in darker regions of photographs than brighter regions. The opposite is true for film. This means that the file size difference discussed here will be far less when shooting with more light, such as when you’re photographing outdoors.

As an example, here is another scene that I photographed first at ISO100, and then at ISO3200:

Though there is still a significant amount of noise in the image, the ISO100 photo has a 15.8MB file size, while the ISO3200 photo is 16.7MB. This means that for this outdoors shot, the higher ISO only caused a 5.7% increase in file size. There’s other factors that will cause this percentage to fluctuate, such as the complexity of the scene, but in general the percentage should be less when photographing with more light.

File Compression

Now that we’ve shown the increased image noise that comes with higher ISO numbers, we’ll discuss why this causes the file size to increase.

Regardless of whether you’re shooting RAW or JPEG, it’s likely your photographs are stored in a compressed format. While some cameras allow you to choose whether and how files are compressed, RAW images (i.e. Canon’s CR2 format) are usually compressed using a lossless algorithm, meaning the exact original data can be reconstructed from the compressed data. On the other hand, JPEG is lossy, so the more you work with JPEG files, the less data you’ll have as the compression throws out more and more data.

Here is a sequence of images from Wikipedia showing lossy compression (with PNGs):

The image on the right is the most compressed, and therefore has the least information. There is no way to recover the original detail from the compressed image to reconstruct the original (on the left), since the information was thrown out in order to save space when compressing the file.

The reason noise increases file sizes is because image compression relies on repetition, or patterns. In images with less noise, there are more areas of consistent patterns (i.e. the clear blue sky) that can be compressed. On the other hand, when noise is introduced, these adjacent areas that could have been grouped together and compressed must be split and stored separately, since the noise introduces randomness that cannot be compressed.

Here are four different 100×100 JPEG squares, saved with the same image quality:

On the left is a square with solid blue, which affords maximum compression and therefore the smallest file size. The second square has two shades of blue, alternating by row, while the third square alternates by column. Due to the way the JPEG format compresses images, the second square can be compressed more efficiently than the third, even though both contain exactly the same number of pixels of each shade. Finally, the last square has artificial noise added in using Photoshop. This noise introduces randomness, which results in the least compression and the largest file size.

Now, for a super simplified example of compression, consider the following “photo” with 3 “pixels”:

Since all three pixels are the same, instead of storing the data for all three, one possible way I could “compress” the photo would be to store the color information once and just remember that the entire range of pixels is that color. (i.e. Pixel 1-3 = Blue)

Now, lets say some “noise” is introduced, which changes the image to the following:

Now I can’t specify a single range and a single color, since the sequence has been interrupted. The best I could do might be to say (Pixel 1 & 3 = Blue, Pixel 2 = Yellow), which obviously takes more information to represent.

This isn’t exactly how image compression works, but hopefully you get the point that randomness interferes with compression.

Conclusion

In this post we showed that increasing ISO causes increased noise, which in turn causes larger file sizes due to inefficient file compression. Many of you more advanced photographers might have known some (or all) of this already, but hopefully it was illuminating for some of you.