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Fixed-point predictive AMBTC image compression
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Paper Abstract

In this paper, the AMBTC image compression method is proposed which employs three alternative weights to predict the initial center. AMBTC is a simple but efficient compression algorithm, whereas in terms of the image with salt and pepper noise, the visual quality is not satisfying provided that the mean value is used as the threshold in each 4×4 block. The possible reason accounting for this drawback is that image pixels are modified while the mean value can only best represent the original image data rather than noise data. On the contrary, the median value is more proper to represent noise data alone, which indicates that the mean value alone is unable to properly represent the whole image added with noise. That is to say, when the weighted sum of the mean value and the median value is taken as the initial center, the deviation of image added with salt and pepper noise will be reduced. What’s more, noises with various intensities are added to each image in the standard database, which intends to search for the optimal center in each block, and make a mapping between intensities and weights. It is feasible for us to directly use three weights and analyze the noise intensity to predict the initial center. PSNR of an AMBTC image is improved with 1 dB on average. In order to further improve the visual quality, we search for the optimal center in the confidence interval around the initial center so that PSNR can be improved by 3 dB. The experimental results reveal that the proposed fixed-point prediction compression algorithm enhances the image quality and reduces the computational cost to a large extent.

Paper Details

Date Published: 3 January 2020
PDF: 9 pages
Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 1137314 (3 January 2020); doi: 10.1117/12.2557294
Show Author Affiliations
Mingming Zhang, Xi'an Institute of Space Radio Technology (China)
Quan Zhou, Xi'an Institute of Space Radio Technology (China)
Yanlang Hu, Xi'an Institute of Space Radio Technology (China)
Juanni Liu, Xi'an Institute of Space Radio Technology (China)


Published in SPIE Proceedings Vol. 11373:
Eleventh International Conference on Graphics and Image Processing (ICGIP 2019)
Zhigeng Pan; Xun Wang, Editor(s)

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