Explore MATLAB source code curated for "中值滤波" with clean implementations, documentation, and examples.
This noise-detection-based median filtering approach first identifies noisy pixels through neighborhood analysis, then applies switching median filtering. Unlike traditional methods, pixels classified as noise are excluded from median filtering calculations for other pixels, effectively removing noise while better preserving image details. Key implementation involves threshold-based noise detection algorithms and conditional filtering logic.
MATLAB implementation of the T algorithm applying center-weighted median filtering to images with comparison between original and processed images, including filter parameter configuration and difference analysis techniques.
Median Filter: Applying a 5x5 processing window to remove noise from corrupted images through pixel value replacement
Weighted Median Filtering: Similar to standard median filtering, but with weighted masks containing specific values/weights instead of uniform ones. Implementation involves mask convolution, pixel sorting, and median selection. The process includes: 1) Defining a 3x3 weighted mask 2) Position mask at top-left corner 3) Multiply and sort pixels 4) Select median value 5) Assign to center pixel 6) Slide mask across image.
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.
A complete MATLAB median filtering program covering nearly all filter types, featuring implementation of various kernel sizes (3x3, 5x5, adaptive) and boundary handling methods, including test results on the standard LENA image dataset.
This study analyzes and compares the advantages and disadvantages of mean filtering and median filtering techniques for color image processing, including implementation approaches and algorithm characteristics.
Custom-developed functions for mean filtering, median filtering, and Gaussian filtering operations with comparative analysis against MATLAB's built-in filtering functions using performance metrics and visual output evaluation
Original median filtering program implemented in MATLAB with noise reduction capabilities for image processing applications
This experiment demonstrates adding Gaussian noise and salt-and-pepper noise to grayscale images, followed by median filtering and mean filtering processing with code implementation details