DWT and SVD based Watermarking Scheme with Circulation

Abstract

The major application for watermark is protecting intellectual property rights. In this paper, a watermark scheme with circulation, based on nonoverlapping discrete wavelet transform (DWT) and singular value decomposition (SVD), is presented. First, the original host image and watermark image are divided into nonoverlapping blocks, respectively and to the former DWT and SVD is applied. Second, the scrambling watermark by Chebyshev chaotic map is embedded into the singular value matrix of original components with circulation. Extracting any consecutive four rows and columns from the blocked watermarked image can get complete watermark information. The quantity of embedded watermark information is large and the original image is not needed for watermark extracting. Both theoretical analysis and experimental results indicate that the proposed method can very effectively resist large degree of geometric attacks and compound attacks, and it is also strongly robust against common image processing attacks.

An adaptive watermarking approach based on weighted quantum particle swarm optimization

“…In the second layer, all SVs of the image are scaled by using a constant scaling factor 0.1 and combined with the SVs of the watermarked image; then, the resultant values are substituted with the original image SVs. Recently, [40] proposed a watermark scheme with circulation, based on non-overlapping DWT and SVD. The basic idea is to divide the original host image and watermark image into non-overlapping blocks, respectively, and to the former DWT and SVD is applied.…”

“…Other works propose a systematic mechanism in choosing the proper values for SF [23,40]. Recently, some works [28][29][30]41] utilize intelligent optimization methods in modifying the SF in an intelligent adaptive way.…”