A robust image watermarking scheme in curvelet domain is proposed. The curvelet transform directly takes edges as the
basic representation element; it provides optimally sparse representations of objects along edges. The image is
partitioned into blocks and curvelet transform is applied to those blocks with strong edges. The watermark consists of a
pseudorandom sequence is added to the significant curvelet coefficients. The embedding strength of watermark is constrained by a Just Noticeable Distortion model based on Barten's contrast sensitivity function. The developed JND model enables highest possible amount of information hiding without compromising the quality of the data to be protected. The watermarks are blindly detected using correlation detector. A scheme for detection and recovering geometric attacks is applied before watermark detection. The proposed scheme provides an accurate estimation of single and/or combined geometrical distortions and is relied on edge detection and radon transform. The selected threshold for watermark detection is determined on the statistical analysis over the host signals and embedding schemes. Experiments show the fidelity of the protected image is well maintained. The watermark embedded into curvelet coefficients provides high tolerance to severe image quality degradation and robustness against geometric distortions as well.
Objective video quality measurement is a challenging problem in a variety of video processing application ranging from
lossy compression to printing. An ideal video quality measure should be able to mimic the human observer. We present
a new video quality measure, M-SVD, to evaluate distorted video sequences based on singular value decomposition. A
computationally efficient approach is developed for full-reference (FR) video quality assessment. This measure is tested
on the Video Quality Experts Group (VQEG) phase I FR-TV test data set. Our experiments show the graphical measure
displays the amount of distortion as well as the distribution of error in all frames of the video sequence while the
numerical measure has a good correlation with perceived video quality outperforms PSNR and other objective measures
by a clear margin.
Because of the transition from analog to digital technologies, content owners are seeking technologies for the protection of copyrighted multimedia content. Encryption and watermarking are two major tools that can be used to prevent unauthorized consumption and duplication. In this paper, we generalize an idea in a recent paper that embeds a binary pattern in the form of a binary image in the LL and HH bands at the second level of Discrete Wavelet Transform (DWT) decomposition. Our generalization includes all four bands (LL, HL, LH, and HH), and a comparison of embedding a watermark at first and second level decompositions. We tested the proposed algorithm against fifteen attacks. Embedding the watermark in lower frequencies is robust to a group of attacks, and embedding the watermark in higher frequencies is robust to another set of attacks. Only for rewatermarking and collusion attacks, the watermarks extracted from all four bands are identical. Our experiments indicate that first level decomposition appear advantageous for two reasons: The area for watermark embedding is maximized, and the extracted watermarks are more textured with better visual quality.