TECHNIQUE | Top 5 Tips for maximum image quality


If you’re looking to take your photography to the next level, maybe even becoming a part-time or full-time pro or perhaps selling some prints, I think there are five things that you should be doing in-camera to ensure that you take advantage of the image quality that your camera has to offer. So, without further adieu, here are my top 5 ways to get great image files.


You don’t have to shoot in RAW; JPEGs are quite capable of producing good images. If you’re a hobbyist and want to produce pictures ready to print and share, get out there and shoot some great pictures in JPEG. But if you’re looking to take your nature photography to the professional level, RAW is for you. Why? JPEG files don’t make use of the vast majority of the information that modern DSLR cameras are capable of capturing; RAW files do and that translates ultimately into more control over image optimization and higher-quality large prints.

Here’s how it works. Each pixel on your camera’s sensor consists of three color channels — red, green, and blue. JPEGs are 8 bit files, which means that 8 bits of binary information (1s or 0s) are possible for each color channel. Raising 2 to the 8th power (for each channel, either a 1 or a 0 is possible 8 times) gives 256 possible combinations for each color channel. Since there are three colors, we take 256 to the 3rd power (red, green, and blue), which yields a total of around 16.7 million possible color values in a JPEG image. Doesn’t sound too bad, right?

But now let’s look at RAW files. Most cameras these days capture RAW files with 12 bits. Using the same math as above, we have 12 possible binary outcomes for each color channel. So, 2 to the 12th power is 4,096. If we take those 4,096 possible tonalities for each color channel and look at all of the possible color values for the three color channels combined, we can take 4,096 to the 3rd power. This yields over 68 billion color possibilities. So, a RAW file has over 4,000 times as much potential color value information as a JPEG file. Put another way, if you shoot JPEG, you’re only using about 2.5% of the possible color information that your camera is capable of recording!

In addition, JPEG files are compressed in a lossy fashion, which means that some of the relatively limited information captured in the first place is thrown away to keep file size smaller. So, on top of the fact that JPEG files start with less information than RAW files, they then throw away some of that information during the compression process. Do note that RAW files also are compressed but using mathematical algorithms that are lossless, meaning that no image data are thrown away in compression in order to reduce file size.

Since JPEG files offer less information for editing in the computer, you’ll most likely want to have the images come out of the camera with saturation and sharpening already applied. Unfortunately, you may or may not like how your camera handles this “post-processing.” Most pros want to be in control of how their images look when they go on the web, for fine art printing, or for a magazine or coffee table book. RAW files take advantage of your camera’s sophisticated image capture capabilities and allow you to stay in control of optimizing your images in the computer.

Posterization is a common symptom when processing a JPEG file of a picture with a colorful sky. Because such skies, especially if the sun is in the frame, exhibit a myriad of very subtle tonal gradations, making changes with limited information can result in image degradation. Because a JPEG file contains much less information than a RAW file, processing it can turn these subtle gradations into abrupt transitions. By way of example, take a look at the comparison below of a sunset image I took in the mountains where I live in Costa Rica. I needed to bring down the highlights and up the saturation in the sky a bit. Processing the RAW file was no problem. When I processed a JPEG version of the RAW file (remember the JPEG has much less color information and is being processed in an 8-bit environment), however, posterization started to become evident. And when I processed a 16 color GIF version of the file, well, let's just say that only Seurat would be happy with the result! The lesson, the more information you start with, the better your final result.

Processed RAW file

Processed RAW file

Processed RAW file, zoomed in

Processed RAW file, zoomed in

Processed JPEG file

Processed JPEG file

Processed JPEG file, zoomed in

Processed JPEG file, zoomed in

Processed GIF file

Processed GIF file

Processed GIF file, zoomed in

Processed GIF file, zoomed in

In addition, RAW files, with their vastly greater information, also give better results when upsampling a file beyond your camera’s native sensor resolution, a necessary practice for selling large fine art prints or doing a gallery exhibit. By way of example, I shot the cloud forest image above with a Canon 20D, an 8 megapixel camera. I was able to work from the RAW file and upsize it for printing at 30 x 45 inches for my gallery exhibit at the Missouri Botanical Garden in the US a couple of years ago. This is fairly extreme upsizing, but the image looked great in the exhibit hall.

 Cloud forest vegetation, Costa Rica


If you don’t use your histogram, you’re putting yourself at risk of underutilizing the information that your fancy DSLR camera (which truly is an amazing machine!) can capture. The histogram allows you to ensure that you’re getting as much tonal information as possible in your images, and it also allows you to focus on capturing the detail you want for certain important parts of any scene. As discussed above, the amount of information in RAW files does allow for a fair amount of post-processing without degrading the image too much. Nonetheless, getting the best exposure possible in-camera is going to mean a better final image, and you’ll also be more satisfied with your effort when you get it right.

The histogram is a big help in this regard but many people seem mystified by it. It’s actually quite simple. The histogram is basically a bar graph in which the x-axis represents the total range of tonal values in a given image from 0 to 255. That is, even in color images, there are 256 possible shades of monochromatic tonalities or luminance values, from pure black (0) to pure white (255). The y-axis indicates the number of pixels having a specific luminance value.

You’ll also see color histograms but most professional nature photographers will tell you that they don’t use these very much if at all. The only time I use them is to check the red channel in a scarlet macaw or maybe the blue in a specific flower or a hummingbird like the violet sabrewing. The consensus among the other pro nature photographers that I know, however, seems to be to master the use of the monochromatic/luminance histogram. Indeed, I have my camera set to display only this histogram by default.

One often hears that a classic bell-curve is a “good” histogram. Nothing could be further from the truth, and as an aside I think the obsession with having no bright highlights and no dark shadows has led in part to the current HDR craze (that’s a story for another post though!). That said, there are many images for which a bell-curve will indeed be a great histogram.

In the nesting toucan image above, for instance, you can see that the majority of the luminance values are clustered in the center of the x-axis. This makes sense because there are a lot of middle-toned greens and earth tones in the image. At the tails of the graph (the left and right edges), there are many fewer pixels with extreme dark or light luminance values. And indeed, the values stop just before the left and right edges of the histogram, meaning that I have detail in the darkest and brightest parts of the image.

As this glass frog image shows, however, there is no one “good” histogram. The correct or optimum histogram will vary depending on the image. Glass frogs are nocturnal so the black background, in addition to being graphically pleasing for this image, is perfectly natural. It gives a very different histogram than the more classic toucan image above but one that is equally correct.

Note that there is a big spike of values pushed up against the left side of the histogram. This means that there are quite a lot of woefully underexposed, pure black areas. I wanted the background to be black, and so it is. You’ll also notice that there are varying luminance values represented by the dark greens and lighter greens in the image but that, importantly, there are no pixels at the right edge of the histogram. Again, this is fine for this image as there are no values that are white or even close to it. Had I put a flash on the leaves in the background in order to make the background green, the histogram would indeed have been closer to a bell-curve. That’s not what I wanted for this image though

Above is another example of a non-traditional histogram but one that is entirely correct for this image. Note here that there is a big spike that bumps up against the right edge of the histogram. This means that there are lots of overexposed highlights; in fact, a spike this big and this close to the edge means that these values are pure white and that they contain no recoverable detail. If I had wanted this image to be a silhouette of bird and tree against a cloudy sky, I would be in big trouble because the whites are blown. Of course, that wasn’t the intention here so the overexposed whites are just fine.


Exposing to the right is a practice that many people don’t follow precisely because RAW files do stand up so well to post-processing. But shooting RAW doesn’t give us an excuse to be sloppy, and exposing to the right is important for two reasons. The first is simple. If you underexpose an image and then have to pull out shadow detail from the darker areas of an image, you’re going to be introducing noise. But darkening slightly overexposed areas will not give you a loss in quality. This is true because of the second reason.

This second reason is even more compelling but requires a bit more explanation. DSLR cameras in general have about five stops of dynamic range. Recall from above that a 12-bit RAW file has 4,096 possible tonal values in each color channel. If we array the stops of dynamic range along our monochromatic or luminance histogram, we’ll notice that each stop (from left to right) contains two times more information than the previous stop. And notice also that most of the possible color values are in the brightest areas. That is, our camera can capture only a relatively few dark tonal values and lots of bright tonal values.

As the figure above illustrates clearly, fully half of the tonal values are in the brightest fifth of the histogram. So, if you don’t have at least some pixels heading out into that rightmost fifth of the histogram, you’re wasting half of the potential tonal information that your camera can capture!

Exposing to the right does not mean overexposing to the extreme though. It simply means that you should expose your image so that the brightest tones in your scene display out into the right fifth of the histogram. If you want detail in the whitest or brightest parts of the scene, however, you need to take care to take them just to the edge of the histogram but not over.

Take the image of a Montezuma oropendola below. This is one of the tougher birds in Costa Rica to expose properly because of the white skin on the face and the black feathers around the head and neck. Underexpose this one, and you’ll have no feather detail in the blacks. Overexpose too far, and the white skin will be blown out white with no detail at all.

Below is a screen shot of my untouched RAW file and the resulting histogram. Notice that there is some space on the left edge of the histogram. This means that the dark feathers are not pure black. And notice that the brightest pixels go right out to the right edge but not past. This means that I made the image as bright as I could in order to capture feather detail in the blacks but without blowing out the white skin. You’ll note also that there is a large amount of pixels clustered toward the middle right of the histogram. This is the background, which is represented by brighter than average mid-tones. The background in this shot was distant forest but there was some fog moving through, which meant that the background was indeed a bright but fairly dull green.

In terms of exposing to the right, there is a caveat that applies especially to the rainforest, where light is usually scarce. Let’s say that I’m shooting a monkey that’s moving around a bit. I have my lens aperture set wide open, I’m getting only 1/60 of a second, and I’m already at ISO 3200. That is, I’m doing everything possible to get just barely enough light for a sharp image. I take a shot and check my histogram and find that I really should be pushing my exposure one stop to the right to get good detail in the monkey’s dark fur. I have a bit of a dilemma now — how to get that extra stop of light.

I can’t open up my aperture any further; it’s already wide open. If I adjust my shutter speed to let in one stop more light, I drop to 1/30. I think that’s going to make it hard to get a sharp image in this situation, and it’s also placing me into the territory where mirror vibration becomes a concern. So, I don’t want to take my shutter speed any slower. I could take my ISO from 3200 to 6400 but, even though my Mark IV is quite good at high ISOs, I’m not enamored of 6400. So, this is a case where not exposing to the right and brightening the exposure in post-processing may actually be a better or at least equally valid choice. I want a sharp image so I need that shutter speed. And going to ISO 6400 will introduce noise, perhaps just about as much as taking the image at ISO 3200 and brightening it by one stop in post-processing.

This, of course, is a fairly extreme situation but it’s worth noting because there are some potential tradeoffs involved when exposing to the right. Still, it’s a good habit to have and will help you to get the cleanest image files possible in the vast majority of shooting situations.


In a digital photography workflow, a principal axiom is that you can start with more and get less but you can never start with less and get more. (It’s not really a famous axiom; I just made it up.) A prime example is taking a tiny 72 dpi JPEG and trying to blow it up to print a poster. It’s not going to work.

Another area where this rule applies is with color spaces. A color space refers for our purposes to a system for representing colors in a numerical form. Adobe RGB and sRGB are the most common color spaces used by today’s DSLR cameras.

The figure above, which is borrowed from the Eizo website (Eizo makes what are probably the best monitors out there but you’ll pay for it), shows how these two color spaces relate to the broader color space that encompasses all of the colors and tones that the human eye can discern. You’ll notice immediately that Adobe RGB is a wider color space or gamut than sRGB, particularly for greens and some shades of blue. By setting your camera to capture your RAW files in Adobe RGB space, you’ll be taking advantage of more color information than if you shot in sRGB. As with the next two parameters I discuss in the following sections, choosing the best setting in-camera will allow you to accurately judge your histogram.

Note that the choice of in-camera color space (again, as with the following two sections below) when shooting RAW does not affect the actual RAW data. If you use Adobe Camera RAW, either in Lightroom or Photoshop, a color space is not truly applied to a file until you convert it to say a TIFF, a PSD, or a JPEG. If you use your camera's own software (e.g., Capture NX for Nikon, or DPP for Canon), the choice of in-camera color space will be read directly and used as the basis for your photo processing.

Just remember, Adobe RGB is the best choice for in-camera setting when shooting RAW for two reasons. You'll have a more accurate histogram and you avoid any potential for being fooled into working with less information in post-processing.

So, does this mean that sRGB is always to be avoided?. On the contrary, whenever you convert an image to a JPEG for use on the web or for a presentation, you’ll be outputting the file as sRGB because this is the color space that best corresponds to the screens on most modern electronic devices. Files sent to the web with an Adobe RGB color profile embedded won't look as good. I save files destined for print (magazines, large prints, etc.) in Pro Photo RGB (an even wider gamut than Adobe RGB) and files destined for electronic distribution in sRGB color space.


This is one piece of advice that most pro nature photographers won’t give you because RAW files do offer you the ability to change white balance in the computer without degrading the image. There are three reasons that I urge you to set your desired white balance in the field, two of which are perhaps a bit capricious but one that has technical importance.

Before I get to the reasons, let’s take a quick look at what white balance means. Every kind of light has a color temperature, which is actually expressed in degrees Kelvin. The light outside on a sunny day is somewhere around 5000 to 5500 degrees Kelvin. For our purposes, we can consider this to be a neutral light. A tungsten light bulb, on the other hand, has a color temperature of around 3000 degrees Kelvin. This is a relatively “warm” light. The light on a cloudy day, especially at higher elevations will have a higher color temperature, say somewhere between 6000 and 7000 degrees Kelvin. This is cool light.

Back in the film days, most films were daylight-balanced, meaning that they were set to record things at a sunny day white balance. Thus, if you used this film to photograph a wedding hall lit by tungsten light bulbs, the resulting images would have an orange color cast. This can be a nice look but if photographers didn’t want it, they would use a blue filter over the lens to increase the color temperature of the light entering through the lens, thus resulting in a more neutral-looking image. By the same token, nature photographers shooting landscapes on a cloudy day in the mountains would often use a warming filter. These amber/orange-colored filters made the cool, bluish light warmer, resulting in a more natural-looking image.

Today’s DSLR cameras handle these issues through the use of white balance settings. You’ll notice that there are a number of presets for tungsten, flourescent, daylight, cloudy, and flash (among others). These presets simply tell the camera to record a given scene at the color temperature that corresponds to each preset’s value. So, daylight white balance on most cameras will be around 5500 degrees Kelvin, cloudy around 6500 Kelvin, and tungsten around 3000 Kelvin. So, if you shoot a daylight beach scene using the tungsten white balance setting, you can get a bluish, moonlit kind of look. Alternatively, you can punch up the colors of a rather cool and anemic sunset by setting your camera on cloudy white balance to bring out more yellows and reds. Of course, you can also set the color temperature manually on most cameras. So, if one of the presets doesn’t work, you can set the camera to record at 2200 Kelvin or 5700 or 9800 — anywhere between 0 and 10,000.

Many people, even many pro photographers (!), use auto white balance, in which the camera tries to evaluate the light and make the best judgement on color temperature. I never use auto white balance for nature as it nearly invariably gives an unattractive bluish/gray look. Others are fans of custom white balance but setting a custom white balance is a cumbersome chore and is best suited, in my opinion, to studio work.

Above is a comparison of how different white balance settings affected my image of a chestnut-mandibled toucan. My original choice was daylight, which I still think is the best. Cloudy is too warm for this scene, and tungsten obviously is absurdly cool. Auto white balance, which is how many people shoot, doesn’t look bad but it’s too gray and cool. Daylight brings the muted green colors of the background and the bright yellow colors on the toucan the closest to how the scene actually was when I took the picture.

Still, auto white balance did a respectable job and, as we’ve been discussing, having shot in RAW would mean that I easily could adjust the white balance in post-processing. So, why worry about setting the white balance in-camera? Why not just use auto as it’s one thing we don’t have to worry about in the field? Here are my three reason for why I think it’s important to set your preferred white balance in-camera.

First, I consider it one of those things that keeps you in the zone as you’re photographing. I’m much more satisfied with my effort if I’ve considered every photographic variable in the field. Not convinced?

Second, I just don’t enjoy looking at auto white balance images on my screen. They look strange, and I have a hard time evaluating if I’m getting what I want. Better, but not quite?

Ok, here’s the third and most important reason. You’re shooting RAW. You know how to interpret your histogram. And you’re exposing to the right. You’re doing everything to get the maximum possible image file quality. The problem is that the histogram is derived from a JPEG. That’s right, even though you’re shooting in RAW format, your camera needs to interpret that data into something you can see, which is the little image on the screen on the back of the camera.

This little image is a processed JPEG that takes into account things such as white balance. The histogram is derived from this little processed JPEG, which means that if you shoot in auto white balance even though you know that’s not the look you’re going to want, the histogram is not accurate. You may be clipping highlights or blocking up shadows sooner or later than what the RAW data show because you are evaluating an auto white balance JPEG.

Let’s take a look at the figure below. This is my toucan shot, with my preferred daylight white balance on the left and auto white balance on the right. The difference is subtle but you can see that auto white balance is actually showing us a brighter histogram. Most values are shifted slightly to the right. This is especially apparent when we consider blown highlights, which is crucial because in this image I wanted to push my exposure as far to the right as possible in order to bring out feather detail in the toucan’s black feathers.

Pay attention to the tuft of white feathers just above the toucan’s tail. Do you notice the bright red areas? Those aren’t on the toucan but rather are blown highlight indicators from Lightroom. I have just a couple of blown spots in the daylight white balance version but quite a bit in the auto white balance version. Though I want to bring out feather detail in the blacks, I’m also very concerned about blowing out the whites.

Had I evaluated the auto white balance histogram in the field, I would have thought “Man, the whites are really starting to blow out. I’d better back off a bit on my exposure.” That would have been a mistake because I wanted the colors that daylight white balance would produce and by evaluating that histogram, I can see that I’m fine — a couple of slightly blown highlights in those white feathers but nothing that can’t be dealt with in Lightroom. Had I backed off on my exposure as the auto white balance histogram was indicating to me, I would have blocked up the dark tones a bit, robbing me of some fine feather detail in the black feathers. I would have ended up lightening the black a bit in post-processing, and this probably would have introduced some noise.

Am I making a mountain out of a molehill? Perhaps, but remember that it’s a competitive world out there, and I want to make sure that I produce the cleanest files possible so that the images I send to magazines are as good as they can be. And I want my fine art prints to be beautiful and full of detail. In a competitive business, every edge that you can give yourself counts. Many photo buyers are quite discerning, and I want them to know that I’m going the extra mile.

By the way, not only does the little JPEG on the back of your camera (and the resulting histogram) take into account white balance but also variables related to picture style. Setting picture style to Vivid in Nikon or Landscape in Canon tends to produce snappy, saturated files that look great on the back of your camera. But if you have sharpening (which increases edge contrast), contrast, and saturation set high, you might think that you are clipping highlights or shadows when in fact the RAW data (which don’t have a white balance or picture style encoded in them) have more latitude than what the histogram is showing you. That’s why most pro nature photographers will have their picture style setting set to neutral or faithful so that their histograms are more representative of the RAW image data.

There are a number of informative articles out on the web covering these subjects in more detail. My friend Greg Downing wrote a great article a few years ago on how to interpret your histogram. Michael Reichman of Luminous Landscape was one of the first to call attention to exposing to the right a few years ago. Nature photographer Ron Day wrote a very clear and concise article on the RAW file format a couple of years ago. The Cambridge in Color website has some wonderful technical tutorials on subjects such as white balance and bit depth.

I hope you’ve enjoyed this post. As always, feel free to leave a comment below.