Commonly Used Contrast Calculation Formulas in Image Processing with Code Implementation

Resource Overview

Implementation of widely-used contrast calculation formulas in image processing, including a canvas expansion method for image transformation that requires minimal code modifications for practical application.

Detailed Documentation

This article provides detailed explanations of commonly used contrast calculation formulas in image processing. The implementation includes key algorithms such as RMS contrast, Michelson contrast, and Weber contrast calculations with corresponding mathematical expressions and code snippets. Additionally, it presents a canvas expansion method for image transformation that can be easily adapted by making minor adjustments to existing algorithms. These methods feature straightforward implementation approaches using matrix operations and pixel value manipulations, ensuring computational efficiency while maintaining image quality. The solutions are designed with modular functions that handle border padding, interpolation methods, and contrast normalization, making them highly applicable in various image processing domains including computer vision and digital photography applications.