Lossless Image Compression through minimizing Spatial Redundancy

Abstract

The growth of digital world has directed to abundance amount of data essential to demonstrate modern imagery. This needs huge amount of space to store data, and minimum bits per pixel for transmission, and both are comparably expensive. These two problems prove the necessity for lossless images compression. Image compression reduce the number of bits to transfer data, the total data to represent the image information and produce a compressed form of an image. The main idea of this work is to reduce spatial redundancy of image data which reduced the requirement of bits per pixel of image for transmission without losing the essential information of it. Proposed algorithm based on lossless compression and minimizing spatial redundancy. Lossless image compression is an essential technique to save storage and cost without losing any data for massive amount of data produce by image applications. New proposed bit shuffled method which enhance the compression ratio and achieving identical results to original image. In the proposed algorithm, image represented as gray coded image. Gray coded image gives more pattern repeated runs in bit planes. Bit shuffle method conducted on bit plane slicing of gray coded image which reduce the spatial redundancy of image. Standard lossless compression algorithms have been implemented on bit shuffled image. Results show that the proposed algorithm achieves good compression ratio compare to standard lossless compression algorithms e.g., Run length coding, Huffman coding and Arithmetic coding.