程序实现 Resources

Showing items tagged with "程序实现"

This MATLAB-based image processing implementation avoids using built-in functions and instead creates custom algorithms for: 1) Grayscale histogram visualization and calculation through pixel intensity counting, 2) Geometric transformations including horizontal/vertical mirroring and shearing using coordinate mapping, 3) Smoothing and sharpening filters via convolution operations with custom kernels, 4) Threshold segmentation using intensity-based pixel classification. Execute the main function and follow interactive prompts to demonstrate each feature.

MATLAB 195 views Tagged

Timing estimation algorithm in OFDM system synchronization using maximum likelihood estimation method. This program implements timing synchronization through maximum likelihood estimation, featuring signal analysis and likelihood function optimization for accurate timing recovery.

MATLAB 208 views Tagged

This program implements the complete LDPC encoding and decoding process with three distinct decoding algorithms: Belief Propagation (BP), Log-Likelihood Ratio BP (LLR-BP), and Min-Sum algorithm. The implementation simulates transmission over an Additive White Gaussian Noise (AWGN) channel and includes code-level explanations of algorithm mechanics, making it particularly helpful for beginners in channel coding.

MATLAB 185 views Tagged

This program implements image binarization, converting a BMP image into a black-and-white image with the additional capability of inverting black and white colors. Key implementation involves thresholding algorithms and pixel value manipulation.

MATLAB 291 views Tagged

Implementation of Gaussian Mixture Model (GMM) background modeling written in MATLAB. While computationally intensive with relatively slow execution speed, this code serves as an educational example demonstrating the core algorithm mechanics. Originally developed during the author's participation in SJTU's PRP program, this implementation is no longer actively used in the original project but remains valuable for learning purposes.

MATLAB 212 views Tagged