Title: Least mean square error-based image compression using block truncation coding

Authors: S. Chandravadhana; N. Nithiyanandam

Addresses: Department of Electronics and Communication, B.S. Abdur Rahman University, Seethakathi Estate, National Highway 45, Vandalur R.F., Tamil Nadu 603210, India ' Department of Electronics and Communication, B.S. Abdur Rahman University, Seethakathi Estate, National Highway 45, Vandalur R.F., Tamil Nadu 603210, India

Abstract: Block truncation coding is one of the image compression techniques which has low computational complexity. This lossy compression technique divides the image into equal block sizes and the pixels in each block are replaced with a high mean and low mean value based on the mean as the threshold. The bit plane thus obtained after quantisation is transmitted along with the mean and variance. This gives a bit rate of 2 bits per pixel. Nevertheless, when the block size is increased for obtaining higher compression ratio, the image is dominated by severe blocking artefacts and blurred edges thereby reducing the visual quality of the image. In the proposed method the mean square error is calculated iteratively for the blocks. The pixels are grouped into higher order and lower order blocks and the group which produces the least mean square error is transmitted along with the mean values of the higher order and lower order block. This implies that the image which is retrieved in the receiver gives the optimised visual quality in the least mean square sense.

Keywords: block truncation coding; BTC; image compression; blocking artefacts; compression ratio; bit plane; bit rate; quantisation; mean; variance; least mean square error; LMSE.

DOI: 10.1504/IJICT.2017.085459

International Journal of Information and Communication Technology, 2017 Vol.11 No.1, pp.25 - 37

Received: 23 Apr 2014
Accepted: 08 Oct 2014

Published online: 21 Jul 2017 *

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