MATLAB Code Implementation for Image Denoising

In the field of image processing, image denoising is a critical task aimed at improving image quality and clarity by eliminating noise. One commonly used denoising technique is Gradient Reciprocal Weighted Filtering. This method calculates image gradients and applies weighted processing to pixels based on gradient values to achieve noise reduction. In MATLAB, this denoising approach can be implemented using specialized code that typically involves gradient calculation functions (like imgredient), pixel weighting algorithms, and filtering operations. The implementation generally follows these steps: 1) Compute horizontal and vertical gradients using Sobel or Prewitt operators, 2) Calculate reciprocal weights based on gradient magnitudes to preserve edges while smoothing noise, 3) Apply weighted averaging to neighborhood pixels using convolution operations (conv2 function). Key MATLAB functions involved may include imread for image input, imgradient for gradient computation, and custom weighting algorithms implemented through matrix operations.