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Improving BTC image compression using a fuzzy complement edge operator
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DOI：10.1016/j.sigpro.2008.07.004.png)
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Abstract
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A simple and easy to implement technique for improving block truncation coding (BTC) is proposed. The method is based on replacement of bit block obtained using the conventional BTC method with the fuzzy logical bit block (LBB) such that the sample mean and standard deviation in each image block are preserved. This fuzzy LBB is obtained from the fuzzy edge image by using the Yager involutive fuzzy complement edge operator (YIFCEO). The input image is encoded with the block mean and standard deviation and the fuzzy LBB. Experimental results show an improvement of visual quality of reconstructed images and peak signal-to-noise ratio (PSNR) when compared to the conventional BTC. The raggedness and jagged appearance and the ringing artifacts at sharp edges are greatly reduced in the reconstructed images. With the use of YIFCEO, the proposed method is shown to be more flexible to determine the visual quality of the reconstructed images. (C) 2008 Elsevier B.V. All rights reserved.
Keywords:
block truncation coding
fuzzy complement
membership function
edge image
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