Explore MATLAB source code curated for "图像修复" with clean implementations, documentation, and examples.
Implementation code for wavelet domain image inpainting using nonlocal total variation algorithm, based on "WAVELET INPAINTING BY NONLOCAL TOTAL VARIATION" by Xiaoqun Zhang and Tony F. Chan, Inverse Problems and Imaging, 2010, 4(1). This MATLAB implementation combines wavelet decomposition with nonlocal regularization for effective image restoration.
Image Processing Technique for Image Restoration Based on Regional Texture Synthesis
The TV model for image inpainting achieves superior image restoration results using partial differential equation-based methods, with implementations typically involving gradient descent optimization and regularization techniques.
This source code package provides comprehensive image processing capabilities including image denoising, image inpainting, and PSNR calculation, primarily implemented using total variation methods and other advanced techniques.
MATLAB source code for image inpainting using Total Variation (TV) method, featuring heat diffusion restoration and multi-scale approaches with detailed algorithm implementations and function descriptions.
Implementing partial differential equation approaches for image restoration, capable of processing both grayscale and color images with algorithm-driven pixel reconstruction
Implementation of image inpainting using T. Chan's Total Variation (TV) method, with code-level discussion on its algorithmic limitations in handling visual connectivity issues.
A methodology employing CDD (Contextual Data-Driven) techniques for restoring damaged grayscale or color images with implementation insights
Implementation of image inpainting suitable for large damaged areas. This algorithm utilizes exemplar-based image inpainting for region filling and object removal, operates in CIE Lab color space for improved color perception alignment, and was originally published in IEEE 2004. The MATLAB implementation includes priority-based patch selection and texture synthesis mechanisms.
The BSCB model is designed for image inpainting, simulating manual restoration processes using partial differential equations (PDEs) with numerical implementation techniques.