Median Filtering, Mean Filtering, and Least-Squares Filtering for 3D Point Cloud Data
Implementation methods for median filtering, mean filtering, and least-squares filtering of 3D point cloud data with code-level processing approaches
Median Filter, Mean Filter, and Wiener Filter: Comparative Analysis and Implementation
A comprehensive comparison of Median Filter, Mean Filter, and Wiener Filter with code implementation insights
Effectiveness of Mean Filtering on Gaussian Noise with Code Implementation
Mean filtering performance on Gaussian noise, 2D adaptive Wiener filtering effectiveness for Gaussian noise removal, comparative analysis of mean/median/Wiener filters on salt-and-pepper noise, 2D statistical filtering applications for both noise types, image denoising using wrcoef2 function with MATLAB implementation examples
Gaussian White Noise Removal Using Mean Filtering
Implementation of mean filtering for Gaussian white noise removal in MATLAB, median filtering for noise reduction, and frequency domain low-pass filtering using ideal low-pass filters with code examples and algorithm explanations.
Traditional Filtering Methods such as Mean Filtering
Traditional filtering methods including mean filtering, median filtering, and Wiener filtering for image denoising, along with adaptive median filtering approaches for noise removal.
MATLAB Code Implementation for Image Processing
MATLAB Image Processing with Code Implementation - Includes image smoothing (mean and median filtering) and image sharpening (Laplacian, Roberts, Prewitt, and Sobel operators) with algorithm explanations and key function descriptions.
Custom Median and Mean Filter Source Code Implementation
Recently developed custom source code for median and mean filtering algorithms, now sharing with the community for educational and practical applications.
Median, Mean Filtering, Adaptive Median Filtering, and an Improved Salt-and-Pepper Noise Filtering Program
This program package contains implementations of median filtering, mean filtering, adaptive median filtering, and an enhanced salt-and-pepper noise filtering algorithm. The first three methods serve as benchmarks for comparison with the fourth method, which demonstrates superior performance in removing salt-and-pepper noise from images. All implementations include efficient matrix operations and sliding window techniques for optimal image processing performance.
Mean Filtering, Weighted Filtering, Median Filtering - MATLAB Examples
MATLAB implementation examples for mean filtering, weighted filtering, and median filtering techniques applied to image and signal processing applications
MATLAB Implementation of Image Smoothing Algorithms
Custom implementation of image smoothing algorithms: mean filtering and median filtering with various kernel sizes to achieve optimal image output results, demonstrating key techniques in spatial domain filtering.