Converting Grayscale Images to Pseudo-Color Images with MATLAB Implementation

This MATLAB-implemented code is designed to convert grayscale images into pseudo-color images. To understand the implementation, we first need to clarify the fundamental concepts: grayscale images contain pixels with single intensity values, while pseudo-color images assign distinct colors to different gray levels to enhance visual perception of image details. The core algorithm implemented in this code maps grayscale pixel values to a predefined color space using MATLAB's built-in colormap functions. The conversion process typically involves these key steps: reading the input grayscale image matrix, normalizing pixel values to the range [0,1], applying a color mapping transformation using functions like imagesc() or ind2rgb(), and generating the output pseudo-color image. A significant advantage of this implementation is the customizable color mapping parameters. Users can modify the colormap scheme (e.g., jet, hot, parula) through MATLAB's colormap editor or programmatically adjust color transition points using linear interpolation methods. This flexibility allows for tailored visualization suitable for various applications such as medical imaging, thermal analysis, and scientific data representation. The code structure includes essential error handling for invalid inputs and supports multiple image formats through MATLAB's imread() function. Additionally, the implementation provides optional parameters for controlling color saturation levels and output image resolution. This implementation serves as both an educational tool for understanding image processing concepts and a practical solution for enhancing grayscale image visualization in technical applications.