Designing a Suite to Implement Compression and Security Algorithms for Data and Image

Abstract

This project focuses on implementing and comparing the various algorithms of data compression and image compression on the basis of various parameters like efficiency, compression ratio, number of bits etc. This report covers Shannon Fano, Huffman algorithms as a part of data compression techniques and Bit Plane Slicing as a part of image compression techniques. Additionally I have added image reconstruction from its Bit planes. With this report the compression technique has been investigated to yield results on their efficiency, and a discussion is presented as to what issues have brought to bare on their efficiency results. Data compression has emerged as an important enabling technology in a wide variety of communication and storage applications, ranging from disk doubling operating systems that provide extra storage space to facsimile standards that facilitate the flow of business information and to the high definition audio and video standards that allow maximal use to be made of scarce satellite transmission bandwidth. Bit Plane Slicing is the technique in which instead of highlighting gray level ranges ,highlighting the contribution made to total image appearance by specific bits may be desired. Separating a digital image into its bit planes is useful for analyzing the relative importance played by each of the image, a process that aids in determining the adequacy of the number of bits used to quantize each pixel.