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Study on Coding Models for Lossless Compression

G. Sowmiya, N. Ajitha

Abstract


Digital Image Processing is a rapidly evolving field with growing applications in Science and Engineering. The rapid growth of digital technology has motivated the need for better compression algorithms. Image compression is the application of data compression on digital images. In effect, he objective is to reduce redundancy of the image data in order to be able to store or transmit data in efficient form. There are many applications based on image compression, such as document, medical images, magnetic resonance imaging (MRI) and radiology, motion pictures etc. Lossless image compression techniques preserve the information so that exact reconstruction of the image is possible from the compressed data.  This paper presents various coding models for lossless image compression.


Keywords


Lossless Compression, Arithmetic Coding, Huffman Coding, LZW Coding, Run Length Encoding, Redundancy, Weights, Code-to-String, Pair of Form.

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References


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