Image Grayscale Transformation and Arithmetic Operations

Resource Overview

Perform addition, subtraction, multiplication, and division operations on two distinct images; utilize the imadjust function for grayscale transformation; conduct additive noise removal experiments; implement grayscale transformation using linear transformation formulas and master histogram analysis for image processing

Detailed Documentation

In this article, we will explore how to perform addition, subtraction, multiplication, and division operations between two different images using pixel-wise arithmetic operations. We will demonstrate how to use MATLAB's imadjust function to adjust image intensity values by mapping the original grayscale range to a new range, enhancing contrast and brightness. Additionally, we will conduct experiments on removing additive noise through techniques like image averaging or filtering algorithms. To deepen understanding of image processing, we will implement grayscale transformations using linear transformation formulas (such as s = ar + b, where r is input pixel value and s is output) and learn to analyze image characteristics using histograms for intensity distribution visualization. This comprehensive guide will provide hands-on opportunities to develop deeper insights and practical skills in digital image processing.