MATLAB Source Code for Image Grayscale Histogram Processing
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Resource Overview
Custom MATLAB source codes implementing five grayscale histogram processing methods: weighted distance, cumulative histogram, Euclidean distance, histogram intersection, and central moments approach. These implementations provide algorithm-level solutions for histogram analysis and comparison tasks.
Detailed Documentation
This collection contains MATLAB source codes for grayscale histogram processing in digital images. The implementation covers five distinct methodologies: weighted distance calculation for histogram similarity measurement, cumulative histogram computation for distribution analysis, Euclidean distance metric for histogram comparison, histogram intersection method for pattern matching, and central moments approach for statistical feature extraction. Each method includes proper histogram normalization and handles edge cases for robust performance. Users can select the appropriate algorithm based on their specific requirements for image analysis tasks, such as image retrieval, classification, or quality assessment. The code structure follows MATLAB best practices with clear input/output parameters and includes comments explaining key computational steps.
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