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
Segmentation of Adherent Cell Images
Simulation of an international conference paper focusing on implementing segmentation algorithms for adherent cell images using image processing and machine learning techniques.
Fuzzy Kernel Clustering: Algorithm Implementation and Applications
Implementation of fuzzy kernel clustering with supporting research papers for effective fuzzy clustering segmentation of data and images, demonstrating satisfactory performance in practical applications
Edge Detection Based on MATLAB for Image Processing
MATLAB-Based Image Edge Detection Implementation Using Algorithmic Approaches and Built-in Functions
Feature Extraction from Spatial Satellite and Aircraft Images
Feature extraction from spatial satellite and aircraft images, including area, perimeter, compactness, and eccentricity metrics with implementation approaches
Image Contour Extraction Using Wavelet Transform for Registration
This program employs wavelet transform methodology to extract image contours for registration purposes. The implementation first detects edges using wavelet decomposition, identifies the longest continuous contour, computes curvature at sampled points, and performs data matching to determine optimal transformation parameters for precise image alignment.
Computing Optical Flow Fields Between Adjacent Frames in Videos or Images
Calculate optical flow fields between consecutive frames in video or image sequences using a polynomial expansion method. After configuring the video path, simply execute the algorithm for streamlined optical flow computation with practical implementation ready for deployment.
Image Fusion Implementation Using Laplacian Pyramid
This source code implements image fusion based on Laplacian pyramid decomposition, featuring multi-scale image processing and detail preservation algorithms.
Double Random Phase Encoding and Decoding for Images
Implementation of double random phase encoding and decoding for images, including source image processing, encrypted image generation, and decrypted image recovery with code-level technical insights
Implementing Inverse Perspective Mapping for Image Transformation
To perform inverse perspective mapping on images, camera height, field of view, and the desired output image's horizontal width (in meters) must be specified. With accurate parameters, high-quality inverse perspective transformed images can be generated. Key implementation involves calculating homography matrices using OpenCV's warpPerspective function with properly configured projection parameters.