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Performing histogram equalization on acquired color images enables uniform distribution of luminance levels across the image, typically implemented through separate channel processing or color space conversion approaches.
Brightness represents the luminance level of an image, while color refers to its chrominance, encompassing both hue and saturation. This code automatically adjusts these three parameters through histogram equalization and color space transformation algorithms to achieve optimal image enhancement.
Perform differential operations on color images with RGB and luminance histogram analysis, identifying zero second-derivative points through custom algorithm implementation achieving optimal results
Color image fractal compression determines the matching position between R-blocks and D-blocks in one of the R, G, or B channels. The other two channels perform matching at the same D-block location while only adjusting their respective brightness and offset parameters. This approach reduces computational time compared to the Separate Fractal Compression (SFC) method by sharing spatial domain block matching results across color channels.
Based on the contrast sensitivity from EF characteristics (spatial frequency response curve), this method performs 2D multi-level wavelet decomposition on images. From the decomposed wavelet components, it extracts corresponding luminance, sharpness, and correlation metrics for each frequency band. The geometric mean of these three metrics is then arithmetically averaged with the inner product of frequency band weighting coefficients to form a comprehensive image quality evaluation metric.
Implementation of image processing GUI programming using MATLAB toolbox with the following functionalities: 1) Image reading and saving 2) Brightness and contrast adjustment through interactive GUI 3) ROI selection using mouse interaction 4) Image scaling with nearest-neighbor and bilinear interpolation algorithms 5) Histogram statistics and equalization 6) Noise addition and filtering algorithms for denoising