Digital image self-recovery algorithm based on improved joint source-channel coding optimizer
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The purpose of the digital image self-recovery is to restore high quality images as much as possible when the image is tampered. Existing algorithms can only achieve high recovered image quality with tiny tampering rate. To obtain high recovered image quality with large tampering rate, this paper proposes a digital image self-recovery algorithm based on improved JSCC (Joint Source-Channel Coding) optimizer. The algorithm performs quadtree decomposition of original grayscale image corresponding to different decomposition factors γ and performs bit-plane layering according to the block class obtained by quadtree decomposition. Size of each bit-plane is the number of pixels of each block class. Then, the original image is compressed by SPIHT, and the compressed bit-stream of SPIHT is segmented into bit-plane according to the size in order. The bit-planes are protected by different RS (Reed-Solomon) coders to get optimal decomposition result of corresponding γ. Finally, JSCC optimization is designed to get an optimal quality of recovered image. Experimental results show that, using our algorithm, for 2-LSB embedding, when the tampering rate is less the minimum TTR (Tolerable Tempering Rate), the PSNR is improved by 4.93dB. When the tampering rate is larger the minimum TTR, the PSNR is improved by 2dB. When 3-LSB watermark are embedded, the PSNR of recovered image is improved by 2.58dB on average. It shows that our improved optimizer effectively improves the quality of the recovered image at high tampering rates, compared with the similar algorithms.
KeywordsImage authentication recovery SPIHT coding RS coding Quadtree decomposition
This work was funded by National Statistical Research of China (No. 2015LZ59), Key Projects of National Natural Science Foundation of China (No. 61433012), Qingdao Scientific Development Plan of China (No. KJZD-13-28-JCH), Natural Science Foundation of Shandong Province of China (No. ZR2014JL044). The authors is deeply grateful to everyone who contributed to this work, including the respectable reviewers for constructive comments, editors’ hard working, Mrs Yang for theoretical supporting, structural construction, experimental analysis and logical expression, Mr Yan for language editing and writing assistance, Mr Wang for technical editing, Mr Yan, Mrs Zhao and Mrs Yang for helping with acquisition of funding.
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