Converting Binary Images to Grayscale Using Neighborhood Average Two-Dimensional Histograms
Transforming binary images into grayscale representations by employing neighborhood average 2D histograms to preserve enhanced image detail and information
Hough Transform Line Detection Source Code Implementation
Application Context: Hough Transform is a fundamental technique in image processing for identifying geometric shapes from images, widely applied with numerous improved algorithms. Primarily used to extract geometric shapes (such as lines, circles) sharing common characteristics from images. The basic Hough transform detects lines in binary images. Key Technology: Given a line drawn on a binary image, locating its position mathematically using the equation y=k*x+b where k (slope) and b (intercept) are parameters. All lines passing through point (x0,y0) satisfy y0=kx0+b, meaning each image point defines a line family in parameter space. Code implementation involves mapping edge pixels to parameter space curves and detecting intersections through accumulator arrays.
MATLAB Code Implementation for Image Binarization
This program implements image binarization, converting a BMP image into a black-and-white image with the additional capability of inverting black and white colors. Key implementation involves thresholding algorithms and pixel value manipulation.
Pseudo-color Processing: Converting Grayscale Images to Color Images
Pseudo-color processing refers to the conversion of grayscale (black-and-white) images into color images or the transformation of monochromatic images into images with specified color distributions. Since the human eye can distinguish colors much more effectively than shades of gray, converting grayscale images to color representations improves the ability to detect image details. The fundamental principle involves mapping each grayscale level to a specific point in the color space, enabling the transformation of monochrome images into color images by assigning distinct colors to different gray levels. In code implementation, this typically involves creating a color lookup table (LUT) where grayscale values are mapped to RGB triplets using linear or nonlinear transformation algorithms.