Reading and Processing Images in MATLAB with PSNR Calculation
- Login to Download
- 1 Credits
Resource Overview
Detailed Documentation
This article demonstrates how to utilize MATLAB for reading images and calculating their Peak Signal-to-Noise Ratio (PSNR). PSNR serves as a crucial metric for evaluating image quality, representing the ratio between meaningful information and noise contamination. By computing the PSNR value, we can objectively assess image clarity and degradation levels. The implementation involves MATLAB's built-in functions: the imread() function for loading image data into the workspace, and the psnr() function for quantitative noise measurement. The imread() function supports various formats (JPEG, PNG, TIFF) and returns a matrix representing pixel values, while psnr() compares the original image against a processed version using logarithmic decibel scale. Through these methods, we gain deeper insights into image characteristics, enabling refined analysis and processing workflows for computer vision applications.
- Login to Download
- 1 Credits