Dynamic Range And Granularity. Dynamic range is important. It is defined as the difference between light and dark areas of an image. All digital images.

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Presentation transcript:

Dynamic Range And Granularity

Dynamic range is important. It is defined as the difference between light and dark areas of an image. All digital images have a maximum and minimum digital value. The minimum is always zero. The max varies according to the bit-depth. An 8-bit color channel has a maximum brightness value of 255. BUT, the brightness values referenced by the values are not typically linear. A curve is applied to the RAW data in order to expand the Dynamic Range. This curve is called the “Gamma Curve”. The math is simple: Out = In Y where “Y” is Gamma This, for obvious reasons it is often called a “power curve”. Gamma is commonly 2.2. Most monitors use that value and cameras all use the sRBG color space which has a 0.45 Gamma built into it. Those two Gamma values are complementary. A camera encodes the linear RAW data and the monitor applies the inverse function to recover the original, linear image. The apparent DR is increased by doing this.

When you examine a histogram, you can usually tell if you have exposed correctly. These simple histograms show 3 different exposures: Note that there are times when a scene is not “balanced”, as when bright or dark elements dominate. But even then, the range of brightness values in the scene should cover the entire histogram, as this allows you to use all the “granularity” your camera has. More on “granularity” later…

It’s easy to “fix” Overexposed and Underexposed images by simply making the Histogram fill up the box. There are Basic sliders in LR that will do this.

BUT, it’s MUCH better to correct the exposure before you take the picture! A greatly underexposed or overexposed image throws away some of the bits, limiting both Dynamic Range and granularity. A common technique is to take a test image and look at the Histogram, then make an adjustment to the camera settings. Repeat this until the histogram is centered. If the Dynamic Range exceeds the capability of your camera, then you have three options: 1.Decide whether the highlights or the shadows are more important for the image and ETTR or ETTL as needed. 2.Reduce the contrast. 3.Take more than one picture and combine them later to get more DR. This is commonly called an “HDR” [High DR] process. Some cameras have a built-in “HDR” mode, but a few don’t do it well. Check to see HOW your camera actually does “HDR” internally. The classical method of taking 3 images at -2 EV, 0 EV, and +2 EV works wonderfully. But this only works on stationary subjects and requires a tripod.

Theoretically, by using a 2.2 Gamma scheme, an 8-bit image should be capable of capturing an 18-stop [or EV] Dynamic Range. In actual use, the best we can get from a JPEG is about 12 EV; the norm is about 8 EV. However, with 14-bit RAW files ALL the DR can be there; we just can’t see it because our output devices [monitors and printers] don’t allow it. SO, why is DR such a big deal? Because it allows incredible latitude when editing! With RAW files, we can make BIG changes w/o creating artifacts, like banding. Banding normally occurs in bright parts of a picture, because of the non-linear encoding; sRGB w/ Gamma = 2.2 uses more bits on the dark parts than the bright parts. This causes things like the sky to show banding easily. If we edit an image to make it darker, bands quickly appear. The 8-bit, sRGB image on the right was edited in LR by moving the Exposure slider to Look closely and you will see banding.

Some JPEG images have TERRIBLE banding after being edited: The way to avoid these is to expose images in such a way as to use ALL of the Dynamic Range available, regardless of what the image looks like OoC. That means save high- bit-depth RAW images and edit them to produce the final JPEG product. Why did I say, “with 14-bit RAW files ALL the DR can be there”? Simply because the bit- depth doesn’t correlate to DR! The DR is controlled mostly by two things: 1.The size of the electron “well” of the photosites [the size of the white #] 2.The amount of dark noise associate w/ the sensor design [the size of the black #] The bit-depth affects the “granularity” of the data [how small the steps are].

Camera manufacturers have control of both the DR and the granularity. They juggle them to give the best results within their budget for the product. The picture on the previous page showed the effect of having too little granularity; the sky was not a continuous, smooth gradient from bright to dark. But the DR of that image was not bad; it might have been hard to tell, since there were scant bright elements. The histogram of that image looked like this: histogram is the sky. I found the original image on a DPR Forum thread and the cause of this banding is clear. The photographer cropped then edited the image to make it MUCH darker. In doing this, he exposed the limited granularity in the bright parts of the sky! Most of the “spiky” part in the middle of the If you want the sky to be a dark, rich blue then you need to expose on it! In this example, the photographer exposed on the foreground and the sky suffered.

Look at the histogram of the original image: This is what you don’t want to see! Notice the big group of bright values jammed up on the right side! The photographer blew out those bright highlights and then could not successfully recover them via editing. In reading the DPR thread, I don’t think the guy ever knew what happened and the dozens of people who attempted to help him, also didn’t understand. There are several answers. One is that his camera [a Sony NEX 5R] simply didn’t have enough DR for that scene. Another is that the photographer saved the picture only as a JPEG, so those bands were “cooked” into the image! And the DR of the JPEG was much less than what a RAW file would have had.