Histogram alternation based digital image compression using base-2 coding

Document Type

Conference Proceeding


Institute of Electrical and Electronics Engineers Inc.


School of Science




Originally published as: Rahman, M. A., Islam, S. M. S., Shin, J., & Islam, M. R. (2019). Histogram alternation based digital image compression using base-2 coding. Paper presented at the 2018 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2018. Original paper available here.


The intention of data compression is to promote the storage and delivery of big images with excellent compression ratio and least distortion. Moreover, the number of internet user is growing day by day speedily. Therefore, the transfer of data is being another significant concern. The storage and the use of an uncompressed picture are very costly and time-consuming. There are many techniques such as Arithmetic coding, Run-length coding, Huffman coding, Shannon-Fano coding used to compress an image. Compression of a picture using the state-of-the-art techniques has a high impact. However, The compression ratio and transfer speed do not satisfy the current demand. This article proposes a new histogram alternation based lossy image compression using Base-2 coding. It increases the probabilities of an image by doing a little bit of change to its pixels level which helps to reduce code-word. This algorithm uses less storage space and works at high-speed to encode and decode an image. Average code length, compression ratio, mean square error and pick signal to noise ratio are used to estimate this method. The proposed method demonstrates better performance than the state-of-the-art techniques. © 2018 IEEE.