期刊名称：Signal & Image Processing : An International Journal (SIPIJ)
印刷版ISSN：2229-3922
电子版ISSN：0976-710X
出版年度：2017
卷号：8
期号：3
页码：15
DOI：10.5121/sipij.2017.8302
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：This paper addresses image enhancement system consisting of image denoising technique based on DualTree Complex Wavelet Transform (DT-CWT) . The proposed algorithm at the outset models the noisyremote sensing image (NRSI) statistically by aptly amalgamating the structural features and textures fromit. This statistical model is decomposed using DTCWT with Tap-10 or length-10 filter banks based onFarras wavelet implementation and sub band coefficients are suitably modeled to denoise with a methodwhich is efficiently organized by combining the clustering techniques with soft thresholding - softclusteringtechnique. The clustering techniques classify the noisy and image pixels based on theneighborhood connected component analysis(CCA), connected pixel analysis and inter-pixel intensityvariance (IPIV) and calculate an appropriate threshold value for noise removal. This threshold value isused with soft thresholding technique to denoise the image .Experimental results shows that that theproposed technique outperforms the conventional and state-of-the-art techniques .It is also evaluated thatthe denoised images using DTCWT (Dual Tree Complex Wavelet Transform) is better balance betweensmoothness and accuracy than the DWT.. We used the PSNR (Peak Signal to Noise Ratio) along withRMSE to assess the quality of denoised images.
