COMPARATIVE PERFORMANCE ANALYSIS OF CONTOURLET TRANSFORM USING NON SUBSAMPLED ALGORITHM IN DIGITAL IMAGE PROCESSING

Abstract: In this paper we have compared Nun Subsampled Contourlet Transform and Wavelet Transform in image denoising on the basis of PSNR, RMSE and SSIM. In order to remove the image noise more effectively an image denoising algorithm based on Non Subsampled Contourlet Transform (NSCT) is proposed. The noisy image is first decomposed into multi-scale and multi-directional subbands by NSCT, and direction subbands of each high-pass component is processed by the new threshold function which is obtained by the Bayes threshold that based on stratified noise estimation. During the reconstruction, the low-pass subband constructed image is further denoisied by the bilateral filtering in the spatial domain. Experimental results compare with the result of image denoising using wavelet transform. It demonstrates that the proposed method can improve de-noising performance.

Keywords: NSCT, PSNR, RMSE, SSIM.