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