Image Quality Metrics GUI: MSE, SNR, and PSNR Evaluation

This GUI-based tool enables comprehensive image quality assessment through three fundamental metrics: Mean Square Error (MSE), Signal-to-Noise Ratio (SNR), and Peak Signal-to-Noise Ratio (PSNR). The interface provides an intuitive platform for analyzing and comparing image quality by implementing mathematical calculations through backend functions. Key implementation features include pixel-wise difference calculations for MSE, ratio computations between original signal power and noise power for SNR, and logarithmic scaling of maximum possible pixel value relative to MSE for PSNR. The GUI framework typically utilizes callback functions to handle image input/output operations and real-time metric updates when comparing reference and processed images. Users can visually track quality variations across different image processing algorithms, facilitating direct optimization and refinement of enhancement techniques. This tool serves as both an educational resource for understanding quality metrics and a practical solution for validating algorithm performance in computer vision applications. The interactive nature allows immediate feedback on how parameter adjustments affect final image quality, supporting iterative improvement of visual outcomes.