Explore MATLAB source code curated for "去噪" with clean implementations, documentation, and examples.
1. MATLAB programming for implementing function reverse sorting using array manipulation techniques; 2. Program implementation of FFT and Inverse Fourier Transform with signal processing algorithms; 3. An image processing application featuring noise addition and denoising filters.
Implementation of an anisotropic adaptive ultrasound image denoising and edge enhancement method, referenced from "Adaptive Anisotropic Diffusion for Ultrasonic Image Denoising and Edge Enhancement.pdf", with the introduction of an additional m parameter for optimized performance.
This practical example demonstrates image denoising through lifting wavelet decomposition, which follows the same fundamental approach as conventional denoising methods by applying threshold quantization to high-frequency wavelet coefficients to achieve noise reduction.
Denoising grayscale and binary images using a morphological filter, which employs fundamental morphological operations to enhance image quality.
Implementation of digital image denoising using neighborhood averaging method (including M-files and sample images with code demonstrations)
Digital filters effectively process EEG signals by removing unwanted components and achieving noise reduction, typically implemented using FIR or IIR filter designs with frequency-selective techniques.
MATLAB implementation of the SRAD (Speckle Reducing Anisotropic Diffusion) algorithm designed for ultrasound image denoising, featuring anisotropic diffusion filtering with edge preservation capabilities.
The Block-Matching and 3D Filtering (BM3D) algorithm is a computationally scalable approach based on an innovative denoising strategy. It achieves state-of-the-art denoising performance in terms of both peak signal-to-noise ratio and subjective visual quality through block-matching, collaborative filtering, and wavelet-based thresholding techniques.
Wavelet transform-based denoising code for image processing, developed as part of a graduation project with implementation details including wavelet decomposition, thresholding techniques, and reconstruction algorithms
Gaussian Low Pass and Gaussian High Pass Filters implemented in MATLAB for image smoothing, noise reduction, and sharpening applications with code implementation details.