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A compressive-sensing based watermarking scheme for sparse image tampering identification

机译:基于压缩感知的稀疏图像篡改识别水印方案

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In this paper we describe a robust watermarking scheme for image tampering identification and localization. A compact representation of the image is first produced by assembling a feature vector consisting of pseudo-random projections of the decimated image. Then, the quantized projections are encoded to form a hash, which is robustly embedded as a watermark in the image. By recovering the watermark the random projections are obtained, and then used to estimate the distortion of the received image. If tampering is sufficiently sparse or compressible in some basis description, a map of the introduced modification is recovered. The system relies on compressive sensing and distributed source coding principles to reduce the size of the hash of a 1024 × 1024 image, to about 4,000 bits. With this hash length, tampering sparse up to 20% and with a tampering energy around a PSNR of 15 dB can be successfully localized.
机译:在本文中,我们描述了一种用于图像篡改识别和定位的鲁棒水印方案。首先,通过组合由抽取图像的伪随机投影组成的特征向量来生成图像的紧凑表示。然后,对量化的投影进行编码以形成散列,该散列作为水印牢固地嵌入图像中。通过恢复水印,获得了随机投影,然后将其用于估计接收图像的失真。如果篡改在某些基础描述中足够稀疏或可压缩,则将恢复所引入的修改的映射。该系统依赖于压缩感测和分布式源编码原理,以将1024×1024图像的哈希值减小到大约4,000位。使用此哈希长度,可以成功地定位高达20%的篡改稀疏,以及大约15 dB的PSNR的篡改能量。

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