MATLAB GUI Implementation of Image DCT with Compression Control and Quality Analysis

This MATLAB GUI application implements Discrete Cosine Transform (DCT) for image processing with customizable compression ratios, Peak Signal-to-Noise Ratio (PSNR) calculation, and graphical comparison of reconstructed images. The implementation utilizes MATLAB's GUIDE (Graphical User Interface Development Environment) to create an interactive interface for image DCT processing. Key functions include imread() for image loading, dct2() for 2D discrete cosine transform implementation, and custom thresholding algorithms to control compression levels by zeroing out high-frequency DCT coefficients based on user-defined ratios. After compression, the system employs PSNR calculation using mean squared error (MSE) metrics via immse() function to quantitatively evaluate image quality degradation. The PSNR algorithm compares the original and compressed images pixel-wise, providing a standard measurement for reconstruction quality assessment. For visual analysis, the application uses MATLAB's subplot() function to display original and reconstructed images side-by-side, along with imshow() for proper image visualization. Additional graphical elements include compression ratio sliders and PSNR value displays created using uicontrol components, enabling real-time parameter adjustment and result comparison. The complete workflow involves: loading RGB images with rgb2gray() conversion, applying block-based DCT processing using blkproc() function, implementing quantization matrices for frequency component selection, and performing inverse DCT (idct2()) for image reconstruction. This comprehensive approach allows users to experimentally determine optimal compression settings while maintaining acceptable image quality through both numerical and visual feedback mechanisms.