Image Compression with Reversible Image Watermarking Scheme Based on Non-subsampled Contourlet Transform and Singular Value Decomposition

Abstract

Image compression is preferred for less storage space, sending image on the internet and often for medical imaging in health industry, technical drawings or comics. Because of wide popularity of sharing media in internet, compression plays a major role in the watermarking algorithm. This paper presents a compression technique through image watermarking algorithm based on Non-subsampled Contourlet Transform (NSCT) and Singular Value Decomposition (SVD). NSCT and SVD both are explored for image watermarking. For image compression, only Singular Value Decomposition is used. The NSCT can give more accurate coefficients of the edges and contours in image which is shift invariant. After getting the coefficients from NSCT decomposition SVD is applied to break the matrix in a convenient way so that image compression can be done without losing meaningful data. The compressed singular values of NSCT decomposed coefficients of cover image are added with the compressed singular values of NSCT decomposed coefficient of gray key image. This helps to improve the performance of the compression using watermarking method. In terms of PSNR and compression ratio, the performance of this scheme is analyzed. The proposed algorithm is robust and suitable for copyright protection and data transmission against compression applications.