MATLAB Implementation of Bilateral Filtering Algorithm
MATLAB code for bilateral filtering with support for both grayscale and color images, featuring clear implementation and easy-to-understand algorithmic structure
Bilateral Filtering and Joint Bilateral Filtering Source Code
Source code implementations for bilateral filtering and joint bilateral filtering - edge-preserving denoising filters with versatile applications in image processing, including pixel similarity-based algorithms and parameter optimization techniques.
MATLAB Implementation of Bilateral Filtering for Edge-Preserving Image Denoising
Bilateral filtering effectively smooths noisy images while preserving edge information through a weighted averaging approach based on both spatial proximity and intensity similarity.
Bilateral Filtering for Color and Grayscale Images: Edge-Preserving Noise Reduction
Implementation of bilateral filtering for color and grayscale images to suppress noise while preserving vital edge information, with code-level parameter optimization insights.
Non-Local Means Algorithm: An Adaptive Spatial Filtering Approach
The Non-Local Means algorithm is an adaptive spatial filtering technique, considered an improvement over Yaroslavsky filtering and bilateral filtering algorithms, with enhanced noise reduction capabilities through weighted similarity comparisons.
Bilateral Filter for Image Enhancement
Implementation of bilateral filter for image enhancement and noise removal, featuring spatial and range domain filtering with customizable parameters.
Bilateral Filtering Implementation for Image Processing
Implementation code for image bilateral filtering algorithm with edge-preserving smoothing capabilities
Bilateral Filtering for Image Processing
Implementation and code for image bilateral filtering technique