N-Square Approach For Lossless Image Compression And Decompression
Matlab, Dot net
There are several lossy and lossless coding techniques developed all through the last two decades. Although very high compression can be achieved with lossy compression techniques, they are deficient in obtaining the original image. While lossless compression technique recovers the image exactly. In applications related to medical imaging lossless techniques are required, as the loss of information is deplorable. The objective of image compression is to symbolize an image with a handful number of bits as possible while preserving the quality required for the given application. In this paper we are introducing a new lossless encoding and decoding technique which even better reduces the entropy there by reducing the average number of bits with the utility of Non Binary Huffman coding through the use of N-Square approach and fasten the process of searching for a codeword in a N-Square tree, we exploit the property of the encoded image pixels, and propose a memory efficient data structure to represent a decoding N-Square tree. Our extensive experimental results demonstrate that the proposed scheme is very competitive and this addresses the limitations of D value in the existing system by proposing a pattern called N-Square approach for it. The newly proposed algorithm provides a good means for lossless image compression and decompression.