Image Compression

In this document, I will discuss key concepts and techniques for image compression using MATLAB. MATLAB serves as a powerful programming language and environment specifically designed for processing and analyzing image data. Image compression refers to methods for reducing the amount of image data to enable more efficient storage and transmission. I will introduce several common image compression algorithms, including both lossless and lossy compression techniques. Additionally, I will explain how to implement image compression in MATLAB through code examples, covering essential functions like imread for loading images, discrete cosine transform (DCT) for JPEG compression, and wavelet transforms for advanced compression schemes. Practical implementation examples will be provided to demonstrate compression ratio calculations using whos command for memory comparison and quality assessment through metrics like PSNR (Peak Signal-to-Noise Ratio). By exploring MATLAB-based image compression in depth, you will gain a solid understanding of fundamental concepts in image processing and data compression, empowering you to apply these techniques to solve real-world problems effectively.