The image below was taken in auto multi-segment mode (left part of Fig.
One wonders – how will the multi-segment (matrix, evaluative) metering handle this? We built a scene similar to a natural winter landscape: the scene has sufficient contrast, has enough white, however, many of the elements of the scene that are compositionally important are darker than the background.
RAWDIGGER HIGHLIGHT ANALYSIS FULL
One of the ways of getting good exposure is metering while using the in-camera spotmeter on the lightest part of the scene that needs to maintain full detail (white clouds, snow, etc.) and applying the appropriate compensation to the exposure recommended by the spotmeter. The exact value for your camera can be found using the method described in the article Establishing the in-camera exposure meter calibration point is the way to extract more dynamic range from your camera. By default, a camera’s spotmeter is calibrated such that between the exposure recommended by the spotmeter and the maximum exposure in RAW there is approximately 3 EV (2.5 EV for JPEG). (Let us note that for a relaxed shoot, one could dispense with such settings and simply use bracketing and rapid result analysis in, for example, FastRawViewer – that is to say, a trial-and-error approach.)Ī photographer, unlike a camera, knows what is important to him in a scene, and therefore when setting exposure, he has the option of using a spotmeter. But all these additional options can only be used if shooting in a very relaxed (shall we say?) manner and with light in the scene not changing at all. Undoubtedly, we could start demanding that camera manufacturers add settings to menus, additional buttons and various other controls. For example, in a contre-jour shot, ought one preserve the background? The photographer knows the answer to this question, the camera doesn’t.
However, when enacting an automatic exposure metering, a camera has no way of knowing the intentions of the photographer and therefore correctly understanding which elements of the scene are important to the composition and which aren’t.
A shot, opened and adjusted in FastRawViewer Not only can it quickly render and display the results of simulating exposure correction, applying white balance, contrast curve, etc., but it will also record these adjustments (as well as any ratings, labels, titles, or descriptions) in an XMP file so as to not have to repeat the aforementioned adjustments in Lr/ACR raw converter.įigure 1. To quickly assess what can be extracted from a shot via a raw converter, we created FastRawViewer. A shot taken at such exposure can be rendered (with the use of a raw converter and a graphic editor) so that the rendering of the scene will match the intention of the photographer and can be presented in the desired size. Good exposure is that exposure which allows you to get high-quality source data – that is to say, with a low noise level and without clipping in the shadows and highlights in all of the elements of the scene that are important to its composition where you intend not to clip but to keep details and texture (of course, if the dynamic range of the scene is wider than the available dynamic range of the camera, it is a purely subjective decision, based on revisualization and if the dynamic range of the camera is wide enough, maximizing the exposure, often called ETTR, is the way to go).
As a rule, these discussions result in the same question – what compensation to automatic metering ought one set to get consistently good exposure? It turns out that no autoexposure mode universally guarantees good out-of-box results. Practically every day, one can see threads on photographic forums where members discuss the various different modes of automatic exposure, trying to find the right one.
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