Explore MATLAB source code curated for "图像复原" with clean implementations, documentation, and examples.
A comprehensive image preprocessing program implementing grayscale transformation, image filtering, image restoration, wavelet transform, morphological processing, and shape recognition with detailed code explanations
Implementation of red-black wavelet for image denoising and restoration, featuring performance comparison with conventional wavelet methods including code implementation insights
Utilizing blind deconvolution image restoration techniques can achieve superior results when restoring blurred images, with implementations typically involving blur kernel estimation and iterative restoration algorithms.
Comprehensive Guide to Image Restoration: Algorithms, Methods, and Code Implementation Approaches for Digital Image Processing
MATLAB implementation of Wiener filtering for image restoration applications with code examples and algorithm explanations
Restoration of images affected by uniform motion blur using computational algorithms and image processing techniques
Image restoration performed with the Lucy-Richardson method, comparing results after 5 and 15 iterations
Image Restoration, Degradation Models, Continuous Degradation Models, Discrete Degradation Models, Algebraic Restoration Methods, Algebraic Restoration Principles, Inverse Filtering Restoration, Least Squares Filtering, MATLAB Implementation of Image Restoration, Wiener Filter Restoration, Regularized Filter Restoration, Lucy-Richardson Restoration, Blind Deconvolution Restoration, Other MATLAB Functions for Image Restoration
A self-developed MATLAB implementation for estimating motion blur direction using Hough transform, containing one well-documented M-file with detailed comments. This resource provides practical insights for image restoration learners, featuring algorithm implementation details and key function explanations for motion blur analysis.
MATLAB-based image restoration source code implementing Wiener filter deconvolution technique, capable of precise restoration for blurred and noisy images through frequency domain processing and noise estimation algorithms.