Getting the correct exposure when shooting with a digital camera is easy. In this article, you will learn what a histogram is, how it can be used to control exposure, and what difficulties you may encounter when determining exposure in practice. I dare to hope that you already know the theoretical basics of exposure and know what shutter speed, aperture, exposure correction, dynamic range, what are the ways of exposure camera and exposure detection modes.
Digital photography is attractive because you can immediately see the image you just took, which makes it very easy to control the exposure. With a digital camera, you don’t have to get into the correct exposure the first time.If the in-camera exposure meter is wrong and the exposure is incorrect, you can immediately find out by looking at the screen and making the necessary adjustments to get the perfect exposure.
The best way to determine exposure accurately and objectively is to use a histogram. This is easier than it might seem at first glance.
The histogram is the most important tool for assessing exposure. All serious digital cameras allow you to see the histogram when viewing images. Sometimes you need to activate the histogram display using the menu.
A histogram is a graph that displays the number of pixels of different brightness for a given image. The horizontal axis indicates the brightness level, from the minimum on the left to the maximum on the right. The vertical axis indicates the number of pixels for each tone.
Correctly exposed scene…
… and its histogram.
Large areas of the same tone image form peaks on the histogram graph. The height of the peak depends on how many pixels have similar brightness. The closer the pixels are in tone to each other, the narrower the peaks are. Light images move the histogram to the right, while dark dark move it to the left. An image containing a full tonal gradient from black to white will have a histogram extending from the left edge to the right.
Pixels that lie within the histogram window are correctly exposed. If they rest on the right or left edge of the window, this means that they are out of the dynamic range.
A large number of pixels at the left edge indicates black shadows that are devoid of detail. If the underexposure is no more than two or three steps, you can try to lighten the shadows in the RAW Converter, but the cost will be to increase the noise level. In fact, pulling shadows in post-processing is somewhat similar to raising the ISO when shooting.
In many images, black shadows are not a problem and look quite natural. This is due to the fact that the human eye is better able to distinguish details in lights than in shadows, and therefore it does not expect much detail from the shadows in the photo.
What’s on the right? If the histogram rests on the right edge of the window, forming a thin peak, this tells us that the lights are hopelessly overexposed. Photodiodes are over-saturated with photons, and any brightness gradations above this limit will be displayed as pure white without a hint of detail. This phenomenon is called clipping and for the human eye, demanding details in the light, it looks very unnatural. Digital photography does not tolerate overexposure. RAW converters allow you to restore minor overexposures, but this is fraught with color distortion and the appearance of rough halos.
Sunset over lake Ladoga.
Here the contrast of the scene is too high. Despite the significant underexposure, the lights are still cut off by clipping.
The histogram can be monochrome or colored. The digital camera sensor generates a three-color image, and therefore I strongly recommend using only a color (RGB) histogram for assessing exposure, reflecting information about the red, green, and blue color channels.
Color histograms for the previous two examples.
The black-and-white histogram shows either the average brightness value in three channels, or it takes information exclusively from the green channel, i.e. it can easily hide the overexposure on the red or blue channel from you. As a result, the accuracy of the exposure assessment falls to ±2 steps, which is completely unacceptable, and the automatic exposure meter usually does not allow such gross errors.
The next five images differ only in exposure: from four times underexposure to four times overexposure in one step (EV). Note the overall appearance of the images, as well as the RGB histogram.
Underexposure at 2 stages (- 2 EV). The histogram shrank to the left of the window. Shadows are radically black, and lights can only be called lights out of politeness.
Underexposure by 1 step (- 1 EV). This is better, but the lightest areas still do not touch the right edge of the histogram window, and they should be almost white. In General, such a picture can be lightened in Photoshop without much loss of quality, but it is better to immediately achieve the correct exposure.
Crocus. Correct exposure.
Perfect. The sun-lit Crocus petals are quite light, but they retain their texture.
Overexposure by 1 step (+1 EV). The histogram begins to lean to the right, and the resulting narrow peak warns us about the loss of details in the lights. This is perfectly acceptable if you want the sun’s glare to be completely white. I don’t think this option is large enough.
Overexposure to 2 steps (+2 EV). Finita. The lights are knocked out and cannot be restored. The crumpled histogram on the right confirms this.
And why not evaluate the accuracy of the exposure of the newly shot frame visually? After all, you can just look at the camera screen. Without ceremony. Moreover, this is the only reasonable way if your camera only offers you a black-and-white histogram. Your eye will be more accurate. An unnatural distortion of colors in the light areas of the frame will tell you about overexposure in individual channels. But keep in mind that a full-fledged, color histogram gives you much more complete control over exposure. It is easy to learn how to use it, and the reward will be the absence of incorrectly exposed images.