Non-Subsampled Contourlet Transform-Based Correlation Denoising
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Addressing noise reduction challenges in image processing, we have developed an innovative denoising method based on non-subsampled contourlet transform correlation. This approach utilizes the non-subsampled contourlet transform as a signal processing tool, which effectively preserves image detail information while achieving superior noise removal performance. Our implementation includes a comprehensive MATLAB toolbox featuring key functions such as nsctdec() for decomposition and nsctrec() for reconstruction, with correlation-based thresholding algorithms applied to transform coefficients. We have conducted extensive simulation experiments that validate the method's effectiveness through quantitative metrics including PSNR and SSIM measurements. The developed non-subsampled contourlet transform toolbox provides researchers with pre-built functions for multi-directional and multi-scale image analysis, facilitating advanced image processing research and applications.
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