Handbook of Image and Video Processing by Alan C. Bovik

By Alan C. Bovik

The instruction manual of photograph and Video Processing encompasses a entire and hugely available presentation of all crucial arithmetic, innovations, and algorithms for all types of photograph and video processing utilized by scientists and engineers. The well timed quantity will offer either the amateur and the professional practitioner with the required details and abilities in order to advance algorithms and purposes for multimedia, electronic imaging, electronic video, telecommunications, and world-wide-web industries.Handbook of photo and Video Processing also will function a textbook for classes resembling electronic snapshot processing, electronic picture research, electronic video, video communications, multimedia, and biomedical photograph processing within the departments of electric and machine engineering and laptop science.KEY gains: * No different source comprises a similar breadth of up to date assurance* comprises over a hundred instance set of rules illustrations* encompasses a sequence of super available instructional chapters* critical for researchers in telecommunications, web functions, multimedia, and approximately each department of scienceAl Bovik is among the top recognized photo processing specialists on the earth. He used to be the host of the 1st IEEE foreign convention on photograph Processing in 1994 and he's the present editor-in-chief of IEEE Transactions on photograph Processing. he's affiliated with the collage of Texas, Austin.

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All of the gray level is compressed to the range [0, log(K)]. However, larger (brighter) gray levels are compressed much more severely than are smaller gray levels. The subsequent FSHS operation then acts to linearly expand the log-compressed gray levels to fill the gray-scale range. In the transformed image, dim objects in the original are now allocated a much larger percentage of the gray-scale range, hence improving their visibility. The logarithmic point operation is an excellent choice for improving the appearance of the image of students, as shown in Fig.

Bovik The University of Texas at Austin Introduction .................................................................................... Notation.. Image Histogram .............................................................................. Linear Point Operations on Images ......................................................... 4 Full-scale Histogram Stretch Nonlinear Point Operations on Images.. 3 Histogram Shaping Arithmetic Operations between Images ....................................................

2 Histogram Equalization One of the most important nonlinear point operations is histogram equalization, also called histogram flattening. The idea behind it extends that of FSHS: not only should an image fill the available gray-scale range, but it should be uniformly distributed over that range. Hence, an idealized goal is a flat histogram. Although care must be taken in applying a powerful nonlinear transformation that actually changes the shape of the image histogram, rather than just stretching it, there are good mathematical reasons for regarding a flat histogram as a desirable goal.

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