Neighborhood Correlation-Based Redundant Second Generation Wavelet Denoising Method

In this document, we present a method that applies the noise reduction concept of wavelet adjacent coefficient correlation to redundant second generation wavelets. By proposing a neighborhood correlation-based redundant second generation wavelet denoising approach, we address the limitation of traditional threshold denoising methods that ignore correlations between wavelet coefficients. This new method not only considers correlations between adjacent coefficients but also effectively handles denoising tasks for redundant second generation wavelets. The algorithm implementation typically involves calculating local correlation matrices within wavelet subbands and applying context-dependent thresholding rules. Through this approach, we can more comprehensively understand and utilize the correlation characteristics of wavelet transforms, thereby improving denoising performance. Key functions in the implementation would include neighborhood correlation computation, adaptive threshold determination based on local statistics, and redundant wavelet transform processing.