(untitled) (International Journal of Engineering and Computer Science, 2017)
Image can be represented with minimum number of bits by using image compression. When images are transferred over the network it requires space for storage and time to transmit image. The present work investigates image compression using block truncation coding. Three algorithms were selected namely, the original block truncation coding (BTC), Absolute Moment block truncation coding (AMBTC) and Huffman coding and a comparison was performed between these. Block truncation coding (BTC) and Absolute Moment block truncation coding (AMBTC) techniques rely on applying divided image into non overlapping blocks. They differ in the way of selecting the quantization level in order to remove redundancy. In Huffman coding an input image is split into equal rows & columns and at final stage sum of all individual compressed images which not only provide better result but also the information content will be kept secure. It has been show that the image compression using Huffman coding provides better image quality than image compression using BTC and AMBTC. Moreover, the Huffman coding is quite faster compared to BTC.