Principios y normas de obligado cumplimiento

Exposing to the right (ETTR) is a technique designed to help photographers maximize image quality. It is only applicable to photographers capturing their images in Raw, where the photographer ‘pushes’ their exposure as close to overexposure as possible, but without actually clipping the highlight areas. The result is a histogram with the majority of pixels grouped to the right of mid-point – hence why it is known as ‘exposing to the right’.

The argument for exposing to the right is best understood once you appreciate that camera sensors count light photons in a linear fashion. Linear capture has important implications for exposure. For example, typically, a digital camera is able to capture around six stops of usable dynamic range (see page 28). Most DSLRs record a 12-bit image capable of recording 4,096 tonal values. However, while you might presume that each stop of the six-stop range would record an equal amount of the tonal value total, this isn’t so. The level corresponds exactly to the number of photons captured so, in reality, each stop records half the light of the previous one.

Linear distribution

At fi rst, this may seem a little confusing and irrelevant. However, in simple terms, what this signifi es is that if you do not properly use the right of the histogram, which represents the majority of the tonal values, then you are wasting the majority of your camera’s available encoding levels. If an image is badly underexposed, you are wasting a

large percentage of the data the camera is capable of capturing. Also, if you then attempt to brighten it during processing, the tonal transitions will not be so smooth and the risk of ‘posterization’ (abrupt changes in tone and shading) is greatly enhanced. However, if you do the opposite so that more data is recorded in the sensor’s brighter stops, you will capture far more tonal information. This is easy to illustrate by simply taking two images – one at a ‘normal’ exposure and the other successfully exposed to the right. Now compare the fi le size; the difference can be several megabytes, with the ETTR image being larger with far more data recorded.

To get the most out of an ETTR fi le, good processing technique is essential (see page 166). The unprocessed Raw fi le will look too bright and washed out. In fact, ETTR images can look quite awful when reviewed on the camera’s monitor, which can deter photographers from using the technique. However, once the image is downloaded onto your computer and exposure, brightness and contrast are adjusted in Raw processing software, the fi nal image will look correct.

Admittedly, ETTR requires more time, thought and effort, but the fi nal result is an image with more tonal information and boasting smoother tonal transitions. Another key benefi t of ETTR is cleaner, less noisy images. To some degree, noise is present in all digital images, even pictures taken at low ISOs. However, it is most obvious in the shadow areas. By biasing the exposure towards the highlights, noise is kept to a minimum.

So, while it remains important not to actually overexpose images to the degree where the value for pure white is blown, when practical to do so, it is always good practice to ‘expose to the right’. While the method needs applying with care, and relies heavily on using the histogram to avoid clipping, image quality is maximized.

E

xpo

su

re

ti

p

‘Exposing to the right’ means biasing your exposures so that the histogram graph is pushed up to the right edge, but not to the point where the highlights are blown. It is a fi ne line between getting this correct and overexposing the image. Apply positive exposure compensation to brighten the image, in small 1/3-stop increments, until the graph is nuzzling the right edge.

■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■ ■

DEH_Ch1.indd 34

35

64 128 256 512 1,024 2,048 levels (half of total)

While the look of your histogram will vary depending on what you are photographing, when adopting the ‘expose to the right’ approach, the majority of the pixels should be right of mid-point. Try to push exposure as close to the right of the graph as possible without ‘clipping’ the value for pure white. The resulting histogram may look similar to this one.

1

2

T

When exposing to the right, the unprocessed Raw fi le may look washed out on the camera’s monitor and when fi rst downloaded onto your computer (1). However, as long as you have used your camera’s histogram screen to ensure the highlights aren’t actually clipped, colour and contrast can be quickly restored during conversion (2).

Nikon D700, 17–35mm (at 17mm), ISO 200, 2sec at f/16, polarizer, tripod.

S

This illustration represents six stops of dynamic range – the typical latitude of a digital camera. The majority of DSLRs are capable of capturing at least a 12-bit image capable of recording 4,096 tonal levels. Half of these (2,048 levels) are devoted to the brightest stop, half of the remainder (1,024 levels) are devoted to the next stop and so on. The last and darkest stop – on the far left of the graphic and representing the shadow areas – has only 64 levels, so is able to record less detail as a result.

DEH_Ch1.indd 35

36

Contrast is a regularly used term, describing the subjective difference in brightness between the light (highlights) and dark (shadows) areas of an image. Photographs with a wide tonal range – with dark shadows and light highlights – are said to be high contrast, while photographs possessing lots of similar shades are regarded as being low contrast.

Contrast is the difference in visual properties that makes a subject distinguishable from other objects and its background. In visual perception, contrast is determined by the difference in the colour and brightness of the subject and other objects within the same fi eld of view. It can have a signifi cant visual impact on our images. High-contrast images have deeper shadows and more pronounced highlights, helping to accentuate texture, shape and a subject’s three-dimensional form. A low-contrast image can appear quite fl at, with little difference in the density of its colours or tones, but appear atmospheric and subtle. Both high- and low-contrast images can work well combined with the right scene or subject.

Contrast is greatly infl uenced by the direction and intensity of light. It is greater under direct lighting conditions; for example, point light sources, such as the sun, or when light is positioned to the side or directly above the subject. If lighting is diffused, or the light source is in front of the subject, the degree of contrast is reduced. A low-contrast image may also result because of the subject matter or conditions; for example, photographs taken in fog, mist or smoke will have little contrast.

An image’s histogram (see page 30) can be used to evaluate its contrast. A broad histogram, demonstrating a wide tonal range from dark to light, refl ects a scene with good contrast. However, a narrow histogram signifi es low contrast and the resulting picture may look fl at. Contrast can be remapped post capture using tools like levels or curves (see page 172). This is useful

in situations where, due to a sensor’s limited latitude, a picture is recorded with less contrast than is faithful to the original scene. Alternatively, you may simply wish to alter an image’s contrast to enhance its impact.