Explore MATLAB source code curated for "灰度化" with clean implementations, documentation, and examples.
Implementing a comprehensive image processing pipeline for pavement crack detection: converting images to grayscale, applying noise reduction filters, enhancing contrast through histogram equalization, differentiating between linear and mesh cracks, and quantitatively measuring crack length (linear) and area (mesh) for damage assessment.
MATLAB image preprocessing including grayscale conversion, logarithmic transformation, histogram equalization, linear smoothing filters, median filtering, adaptive filtering, image sharpening, image binarization, various edge detection operators, and their code implementations
Converting color images to grayscale simplifies data processing by reducing dimensionality and computational complexity
Source code for theoretical foundations of color processing, including grayscale conversion and pseudo-color processing, color adjustment techniques, brightness/contrast modification, color quantization and reduction, dithering algorithms, and enhanced CDib implementations.
Code implementation for license plate recognition featuring grayscale conversion, binarization, feature extraction, and template matching algorithms
He Dongjian - Implementation of Color Bitmap Conversion to Black-and-White (Grayscale) Bitmap with Algorithm Analysis