Image Compression and Watermarking scheme using Scalar Quantization

This paper presents a new compression technique and image watermarking algorithm based onContourlet Transform (CT). For image compression, an energy based quantization is used. Scalar quantizationis explored for image watermarking. Double filter bank structure is used in CT. The Laplacian Pyramid (LP) isused to capture the point discontinuities, and then followed by a Directional Filter Bank (DFB) to link pointdiscontinuities. The coefficients of down sampled low pass version of LP decomposed image are re-ordered in apre-determined manner and prediction algorithm is used to reduce entropy (bits/pixel). In addition, thecoefficients of CT are quantized based on the energy in the particular band. The superiority of proposedalgorithm to JPEG is observed in terms of reduced blocking artifacts. The results are also compared withwavelet transform (WT). Superiority of CT to WT is observed when the image contains more contours. Thewatermark image is embedded in the low pass image of contourlet decomposition. The watermark can beextracted with minimum error. In terms of PSNR, the visual quality of the watermarked image is exceptional.The proposed algorithm is robust to many image attacks and suitable for copyright protection applications.