Image Compression Processing in MATLAB with Source Code Implementation

This is a MATLAB source code example demonstrating image compression processing. While the original description is concise, we can expand on the technical implementation details. Image compression is a fundamental technique for reducing image file size to conserve storage space and transmission bandwidth. In MATLAB, various algorithms and functions can be implemented for image compression, including JPEG compression using discrete cosine transform (DCT) and wavelet-based compression through functions like wavedec2 and waverec2. The implementation typically involves preprocessing, transformation, quantization, and encoding stages. Key MATLAB functions such as imread, imwrite, dct2, and dwt2 can be utilized to analyze and process images while maintaining quality through compression ratio adjustments. Image compression finds extensive applications in digital media, medical imaging, remote monitoring systems, and web optimization. Common implementation approaches include lossy compression (e.g., JPEG) for photographic images and lossless compression (e.g., PNG) for technical diagrams. This source code example provides practical insights into parameter tuning, quality metrics calculation using psnr function, and visualization techniques through imshow. We hope this enhanced example assists in understanding both theoretical concepts and practical MATLAB implementation!