image enhancement


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Related to image enhancement: image restoration

image enhancement

[′im·ij in′hans·mənt]
(computer science)
Improvement of the quality of a picture, with the aid of a computer, by giving it higher contrast or making it less blurred or less noisy.

image editing

Changing or improving graphics images. It typically refers to bitmapped images rather than vector graphics drawings. Using an image editor, images can be modified by an artist using pen, brush, airbrush and other "painting" tools. Filters can be applied, which are algorithms that automatically change the appearance to a selected area of the image. See image editor, image filter and anti-aliasing.
References in periodicals archive ?
To demonstrate the effectiveness of the proposed image enhancement algorithm, we compare it with HE [3], MSR [5], and Soyel's algorithm [15].
These algorithms can be grouped into common categories like image formation algorithms, image enhancement algorithms, morphological operations, feature extraction algorithms, and feature detection algorithms.
Its image enhancement feature provides for screen brightness regulation and contrast tracking when displaying moving images.
OneVision, Regensburg, Germany and Jersey City, N.J., is introducing Amendo, a software solution that provides automated, professional-quality image enhancement, including automated color correction.
State societies requested these ads for the interim period while the national image enhancement campaign is being evaluated.
In medical image enhancement, Preserving Edges are highly important.
Curiously, the news media were not responsible for those barriers; they were erected by fellow administrators who failed to understand how the process of image enhancement really works.
The Institute will use the findings in ongoing image enhancement efforts.
The office space law firms seek must satisfy their guest for both image enhancement and the bottom line.
M2 EQUITYBITES-June 5, 2015-IntelliChief certified with PaperStream IP Image Enhancement Solution
The topics are images, arrays, and matrices; image statistics; transformations; filters, kernels, and fields; image enhancement and correction; supervised classification; unsupervised classification; and change direction.