Your camera captures images with the potential of over 4000 tones between black and white (if captured in grayscale) or 4000 shades of color in RGB. But once the image is captured, the camera’s job is finished. Then the real work begins.
The shadows of early morning lighting caused the detail in this JPEG file to bury all the important shadow detail in the darkness.
The distribution of these tones is your responsibility. Each one of these 4000 tone levels is like photographic currency. Never leave money on the table. Put them all to good use. Here’s where the histogram comes in.
The RAW file of this same shot had plenty of high-bit range to push around and adjust, making my friend appear as though he were in ideal lighting.
But before you can understand the histogram, you must understand how the image sensor in your camera sees light. Image sensors are linear in the way they capture light. Unlike the human eye, the camera’s image sensor registers light by volume; the brightest light hitting the sensor fills that sensor’s light bucket first, occupying over half the available registry.
This may make mathematical sense but that’s where the problem starts. Your eye isn’t a mathematical instrument and it doesn’t quantify light the same way a digital camera image sensor does.
Camera Tonal Distribution
If you look at the way camera sensors register light you’ll see that exactly half of the information recorded by the image sensor (2048 of the 4096 registers) belongs to the brightest of the six stops of light being captured. The next brightest stop records half of the remaining information (1024 registers) and so on.
By the time the darkest stop is recorded, only 64 of the 4096 light registers are left to record all the shadow detail. Since humans quite naturally recognize detail in even the deepest shadows, we notice a lack of detail in these areas instinctively. Over 25% of the image potentially appears very dark and lacking in detail.
Oddly, this lopsided method of capturing light is referred to as linear in that each successive stop records half of the remaining tones in the photo. This ain’t logically linear to the human eye! If the actual balance of human light recognition were expressed as Gamma, it would be gauged at something more like 1.7 and 2.5, depending on the lighting conditions.
Your eye has a nearly infinitely adaptable capacity to register light and is simply more attuned to recognizing detail in low light than your camera.
Let me restate that – your eyes are designed to see more detail in the darker areas than in the extremely light areas. This is completely backward from the way digital cameras record light. This disparity then presents engineers with a significant challenge; how to transpose a linear index into a non-linear or human system.
Because this image was shot toward the sky on a very overcast day, the darker tones lost all detail. But because the image was captured and saved in the camera’s RAW format, the 16-bit color space gave me the ability to adjust many individual settings, recapturing the scene as my eyes remembered it (above).
Out of the 4096 tones that are captured, precious few are left to record critical differences in the darkest parts of an image. The darker tones (since they reflect less light for the image sensor to use) are crammed into a very small portion of the recorded tonal range.
The result is that the three-quarter tones, those found between black and the three-quarter tones almost always appear very dark and lacking in tone separation. Therefore, images that are not adjusted (in post-production) to display low-end tonality will always print dark in the three-quarter tones. Let me say that again – always. A non-linear tonal adjustment is mandatory if your image is to print correctly.
The late afternoon sun off Longboat Key in Sarasota provided ideal warm lighting, allowing me to use the original JPEG format with very few adjustments.
The exception to this statement happens when your image is captured in a controlled lighting environment (like a photo studio) where lights and reflectors can be strategically placed to illuminate shadow areas or when the subject is ideally positioned in outdoor lighting. When carefully arranged lighting is possible, little post-production services may be needed at all. But very few of those ideal lighting scenarios likely exist during your everyday shooting.
JPEG Tone Distribution
Under this controlled lighting JPEGs can produce spectacular results simply because the tone distribution algorithm is designed for ideal lighting conditions. In the absence of ideal lighting though, this algorithm applies the same stock tonal shape to every image assuming that the lighting is perfect.
The result from imperfect (light, dark, or imbalanced) lighting and a JPEG capture is an imbalanced picture containing only a fraction of the editing range of the same scene captured as a RAW image. The editing “elbow room” of a JPEG is severely restricted in color and tone distribution.
The highlights captured by this JPEG image were too blown out to recover.
The same highlights captured and edited in RAW format allowed me to extract full detail in the highlights while retaining all the detail in the shadows as well.
Here’s where the tone distribution-monitoring provided by the histogram can be used to guide the editing process, even from JPEG images. It’s actually a good idea to regard the histogram as a tone map. The histogram will reveal the ratio of tones in the image residing in the lighter or darker portions of the image.
A Word About Bit Depth
Without getting into a long detailed discussion, it is always advisable to shoot both RAW and JPEG images of every scene. This is a simple setting on your camera that requires absolutely no extra effort on your part but provides a much deeper level of tones to push around and rearrange.
This recommendation follows simple logic; RAW images provide more flexibility to adjust the full range of tones while JPEG images are prefabricated one-size-fits-all interpretations of a scene. RAW images are like film-based color negatives while JPEG images are like Polaroids. Negatives (RAW files) can be adjusted freely, Polaroids (JPEGs) are very restricted.
RAW Tone Distribution: The Phoenix Scenario
In Greek mythology, the Phoenix is a long-lived bird that is cyclically regenerated or reborn from apparent oblivion. Used in this sense, any digital image capture that is apparently “dead” by all appearance can have life breathed into it by powerful image editing software.
Such is the case with this image captured during an overcast day in Kailua Hawaii. Absolutely no detail can be seen in this JPEG image; all appears hopeless. A reject, right? Not so fast, quickdraw!
We’re here to raise the dead, remember? While nothing can replace the correct exposure, don’t throw in the towel on an image that looks too dark until you’ve tried this magic collection of tone tools.
Without the extraordinary bandwidth provided by the 16-bit RAW file format, this level of recovery would be impossible.
The image was seriously underexposed and appeared to be hopelessly dark. But when it was opened in both Camera Raw and Lightroom software packages, and the same adjustments applied, identical results were achieved.
Whether the image is captured in jpeg, tiff, or raw format, it can be opened in either of Adobe’s raw interpreter packages, Adobe Camera Raw or Lightroom. Within either of these packages, both chrominance and luminance controls are provided that allow you to rearrange tones and shape images extensively.
To open a tiff or jpeg file in Camera Raw, you must first locate the file in Adobe Bridge, right-click on the file and choose “Open in Camera Raw…” You can open these files in Lightroom either internally or by dragging the file onto the LR icon in the dock.
Camera Raw control panel (left) and Lightroom control panel (right). Top histograms belong to the original while the bottom shows the adjusted image. Both software packages offer virtually identical tools to shape and reconstruct the image.
Recognizing the differences between the way your eyes and your camera sees light will give you a head start on adjusting camera images to more closely resemble the look and feel of the original scene.
