MATLAB Program for Bitmap Binarization of 256 Grayscale Images

MATLAB programs for bitmap binarization of 256 grayscale images are commonly referenced in classical image processing textbooks, now implemented using MATLAB for practical demonstration. Bitmap binarization is a fundamental image processing technique that converts 256-level grayscale images into binary images, where each pixel can only assume one of two values – typically 0 (black) or 255 (white). This conversion is achieved through thresholding operations, where pixels above a specified threshold are set to 255 (white) while pixels below the threshold are set to 0 (black).

In MATLAB implementation, the process typically involves using built-in functions like im2bw (in older versions) or imbinarize (in recent versions) with appropriate threshold selection. The algorithm workflow includes: loading the grayscale image using imread(), determining optimal threshold values using methods like Otsu's algorithm (graythresh()), and applying the binarization function. Key implementation considerations include threshold optimization for different image characteristics and post-processing techniques like morphological operations to enhance binary image quality.

Through these MATLAB functions, users can efficiently convert grayscale images to binary format for demonstration and analysis purposes, while maintaining control over threshold parameters to achieve optimal results for specific applications.