Generally, a still image is a sensory signal that contains significant amounts of redundant information which are represented in their canonical form. Image data compression is the technique and the process of reducing the redundancies in image data required to represent a given quantity of information. As a result, data storage requirements and communication costs are decreased. In digital image compression, data redundancy is the main issue and better compression can be achieved by reducing or eliminating data redundancy. There are three types of basic data redundancies: coding redundancy, inter-pixel redundancy, and perceptual redundancy.
Coding redundancy occurs when the codes assigned to a set of events such as the pixel values of an image have not been selected to take full advantage of the probabilities of the events. Inter-pixel redundancy usually refers to the correlations resulted from the structural or geometric relationships between the objects in an image. Due to the high correlations between the neighboring pixels, any given pixel can be easily predicted from the value or values of its neighboring pixels and the information carried by individual pixels can be relatively small. Any information is said to be perceptually redundant if certain information simply has less relative importance than other information in terms of the human perceptual system. For instance, all the neighboring pixels in the smooth region of a natural image have a very high degree of similarity and this insignificant variation in the values of the neighboring pixels is not noticeable to the human eye.
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