Image Smoothing Processing
Image smoothing effectively removes noise interference, and when combined with sharpening techniques, it can significantly enhance image quality with proper implementation using filters and algorithms.
Explore MATLAB source code curated for "去除噪声" with clean implementations, documentation, and examples.
Image smoothing effectively removes noise interference, and when combined with sharpening techniques, it can significantly enhance image quality with proper implementation using filters and algorithms.
MATLAB implementation for X-CT image processing with wavelet decomposition-based noise removal techniques, including algorithm specifications and function implementations
Achieving effective denoising for images contaminated by mixed noise through comparative analysis of six methodologies, identifying the optimal denoising algorithm with implementation insights.
The Linear Non-Local Means Filter is used in image processing for denoising and smoothing images while effectively preserving edge details through pixel similarity comparisons across the entire image.
Comparative Analysis of FFT-Based Signal Processing and Low-Pass Filtering Techniques for Effective Noise Reduction
MATLAB source code for wavelet transform implementation, designed for speech enhancement applications with effective noise reduction capabilities. Features straightforward algorithm implementation and clearly structured code.
Interpolation Function for Noise Removal in Data Processing
A MATLAB-based program implementing Pulse-Coupled Neural Networks (PCNN) for image denoising, featuring customizable parameters and neuroscience-inspired processing