Phantom Denoising: CS+UWT and CS+NSCT Denoising Techniques

This article provides a detailed discussion of the phantom_denoising method, which incorporates two distinct denoising approaches: Compressed Sensing (CS) combined with Undecimated Wavelet Transform (UWT) denoising, and Compressed Sensing integrated with Non-Subsampled Contourlet Transform (NSCT) denoising. These techniques leverage the sparse nature of signals to preserve critical information while effectively removing noise, achieving superior denoising performance. In practical implementations, the CS component typically involves solving optimization problems using algorithms like L1-minimization, while UWT provides translation-invariant wavelet coefficients and NSCT offers multi-directional and multi-scale decomposition for better texture preservation. The phantom_denoising method has been widely adopted in practical applications and has demonstrated excellent results in the field of image denoising, particularly in medical imaging and scientific visualization where preserving structural details is crucial.