灰度直方图 Resources

Showing items tagged with "灰度直方图"

In digital image processing, the grayscale histogram stands out as the simplest and most valuable tool. It plays a fundamental role throughout the entire workflow—from analyzing and observing images to developing effective processing methods. In programming terms, histograms can be efficiently computed using functions like `cv2.calcHist()` in OpenCV or `imhist()` in MATLAB, which count pixel frequencies across intensity levels to reveal critical image characteristics.

MATLAB 269 views Tagged

This MATLAB-based image processing implementation avoids using built-in functions and instead creates custom algorithms for: 1) Grayscale histogram visualization and calculation through pixel intensity counting, 2) Geometric transformations including horizontal/vertical mirroring and shearing using coordinate mapping, 3) Smoothing and sharpening filters via convolution operations with custom kernels, 4) Threshold segmentation using intensity-based pixel classification. Execute the main function and follow interactive prompts to demonstrate each feature.

MATLAB 195 views Tagged