Performance analysis of Medical Image Compression using DCT and FFT Transforms

There is a high demand for image compression since it reduces the computational time, which in turn reduces the storage and transmission costs. Image compression involves reducing excessive and irrelevant data while maintaining reasonable image quality. Image compression techniques such as the Discrete Cosine Transform (DCT) and Fast Fourier Transform (FFT) are the focus of this study. These tools were selected because of their wide application in image processing; one example is JPEG (Joint Photographic Experts Group), which uses DCT for compression. A comparison is made between DCT and FFT, two compression methods implemented in MATLAB. CT and MRI images are used for an experiment, the quality of an image is determined by various parameters. To perform DCT the filter mask is used and a threshold is used for FFT to keep the top coefficient values. The experimental findings are compared and evaluated in terms of Peak Signal to Noise Ratio (PSNR) and Compression Ratio (CR)