This paper presents a new compression technique and image watermarking
algorithm based on Contourlet Transform (CT). For image compression, an energy
based quantization is used. Scalar quantization is explored for image
watermarking. Double filter bank structure is used in CT. The Laplacian Pyramid
(LP) is used to capture the point discontinuities, and then followed by a
Directional Filter Bank (DFB) to link point discontinuities. The coefficients
of down sampled low pass version of LP decomposed image are re-ordered in a
pre-determined manner and prediction algorithm is used to reduce entropy
(bits/pixel). In addition, the coefficients of CT are quantized based on the
energy in the particular band. The superiority of proposed algorithm to JPEG is
observed in terms of reduced blocking artifacts. The results are also compared
with wavelet transform (WT). Superiority of CT to WT is observed when the image
contains more contours. The watermark image is embedded in the low pass image
of contourlet decomposition. The watermark can be extracted 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.Comment: 11 Pages, IJNGN Journal 201