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For example, in the case of graphical computer displays, contrast depends on the properties of the picture source or file and the properties of the computer display, including its variable settings. For some screens the angle between the screen surface and the observer's line of sight is also important.
Contrast resolution or contrast-detail is an approach to describing the image quality in terms of both the image contrast and resolution. Contrast resolution is usually measured by generating a pattern from a test object that depicts how image contrast changes as the structures being imaged get smaller and closer together.
This method usually increases the global contrast of many images, especially when the image is represented by a narrow range of intensity values. Through this adjustment, the intensities can be better distributed on the histogram utilizing the full range of intensities evenly. This allows for areas of lower local contrast to gain a higher contrast.
The "luminance contrast" is the ratio between the higher luminance, L H, and the lower luminance, L L, that define the feature to be detected.This ratio, often called contrast ratio, CR, (actually being a luminance ratio), is often used for high luminances and for specification of the contrast of electronic visual display devices.
Histogram equalization is a popular example of these algorithms. Improvements in picture brightness and contrast can thus be obtained. In the field of computer vision, image histograms can be useful tools for thresholding. Because the information contained in the graph is a representation of pixel distribution as a function of tonal variation ...
Phase-contrast imaging is the highest resolution imaging technique ever developed, and can allow for resolutions of less than one angstrom (less than 0.1 nanometres). It thus enables the direct viewing of columns of atoms in a crystalline material. [20] [21] The interpretation of phase-contrast images is not a straightforward task.
The basic intent of the contrast enhancement technique is to adjust the local contrast in the image so as to bring out the clear regions or objects in the image . Low-contrast images often result from poor or non-uniform lighting conditions, a limited dynamic range of the imaging sensor, or improper settings of the lens aperture.
The contrast ranges from black at the weakest intensity to white at the strongest. [1] Grayscale images are distinct from one-bit bi-tonal black-and-white images, which, in the context of computer imaging, are images with only two colors: black and white (also called bilevel or binary images). Grayscale images have many shades of gray in between.