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HDR combines three differently exposed images taken in quick succession to create a more arresting image where bright and shadowy elements both have considerable detail.
Examples include the exploration of changing images of disability across time and the analysis of negative images of disability in mainstream literature, art, and film; scholars have uncovered and exposed images that are inadequate, distorted, or contrived.
Differently exposed images are used to estimate the camera response function [1].
In some cases, it is not possible to obtain two different exposed images.
Consequently, a misregistration appears and the linear relationship between two differently exposed images is no longer valid.
Therefore, generally, a post-process called HDR image reconstruction is used, which reconstructs an HDR image from a set of differently exposed images to overcome the limited dynamic range.
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A more sumptuous and correctly exposed image can be obtained by putting a "neutral density" filter on.
Light meters built into most modern cameras measure the subject luminance and set the shutter or the lens diaphragm to yield a correctly exposed image.
Unlike black and white (where it is usually possible to at least extract 'something' of a poorly exposed image) a transparency must be exposed correctly with little room for manipulation in the darkroom.
To do this, the chip's processor automatically takes three separate "low dynamic range" images with the camera: a normally exposed image, an overexposed image capturing details in the dark areas of the scene, and an underexposed image capturing details in the bright areas.
(b) Differently exposed image.
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