Explore MATLAB source code curated for "灰度图像" with clean implementations, documentation, and examples.
A comprehensive MATLAB program for discrete wavelet transform-based image fusion capable of processing grayscale images in any format, featuring multi-level decomposition and customizable fusion rules
Implementation of two-dimensional maximum entropy method for grayscale image threshold segmentation. This practical algorithm includes code-level explanations and implementation considerations for effective image processing applications.
Another corner detection implementation for grayscale images, where corner detection serves as the crucial first step in image matching workflows
Implementation of color transfer from color images to grayscale images using the Welsh algorithm, achieving promising results; This program was developed and debugged in VC++6.0 environment, effectively transferring color characteristics while preserving image structure.
This functionality computes and displays grayscale histograms for both grayscale and RGB images, implementing histogram equalization and processing pipelines for enhanced image analysis.
Automated image reading with preprocessing pipeline including image enhancement, RGB-to-gray conversion, linear grayscale transformation, median filtering, edge detection, morphological operations (dilation/erosion), blue pixel extraction, and final digit segmentation from license plates.
Implementation of grayscale image segmentation using an enhanced spiking neural network approach with code-level algorithm explanations
(1) Visualization of Discrete Cosine Transform (DCT) basis functions as grayscale images (2) Visualization of Discrete Fourier Transform (DFT) basis functions as grayscale images
Denoising of grayscale images, color images, and video sequences using the advanced BM3D (Block-Matching 3D) method, featuring collaborative filtering and hard/soft thresholding techniques.
The upwind scheme in the GAC model effectively segments grayscale images with satisfactory results through gradient-based boundary evolution and level set methods.