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A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image Inpainting

机译:基于SMVQ和图像修复的新型联合数据隐藏和压缩方案

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摘要

In this paper, we propose a novel joint data-hiding and compression scheme for digital images using side match vector quantization (SMVQ) and image inpainting. The two functions of data hiding and image compression can be integrated into one single module seamlessly. On the sender side, except for the blocks in the leftmost and topmost of the image, each of the other residual blocks in raster-scanning order can be embedded with secret data and compressed simultaneously by SMVQ or image inpainting adaptively according to the current embedding bit. Vector quantization is also utilized for some complex blocks to control the visual distortion and error diffusion caused by the progressive compression. After segmenting the image compressed codes into a series of sections by the indicator bits, the receiver can achieve the extraction of secret bits and image decompression successfully according to the index values in the segmented sections. Experimental results demonstrate the effectiveness of the proposed scheme.
机译:在本文中,我们提出了一种使用边匹配矢量量化(SMVQ)和图像修复的数字图像联合数据隐藏和压缩方案。数据隐藏和图像压缩这两个功能可以无缝集成到一个模块中。在发送方,除了图像最左侧和最顶部的块外,其他按光栅扫描顺序排列的剩余块都可以嵌入秘密数据,并通过SMVQ或图像修补根据当前嵌入位同时压缩。 。向量量化还用于某些复杂的块,以控制由渐进压缩引起的视觉失真和错误扩散。接收器将指示符比特将图像压缩后的代码分割为一系列部分后,接收器可以根据分割后的部分的索引值成功实现秘密比特的提取和图像解压缩。实验结果证明了该方案的有效性。

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