Comparison Study for Three Compression Techniques (Wavelet, Contourlet and Curvelet Transformation)

Abstract

Researches and studies on compressing digital images are aiming to make it easier to deal with networks, communications and Internet by reducing the size of the multimedia files transferred, and reducing the execution time and transmission time. In this research, the lossy compression method was adopted as one of the solutions that reduce the size of the data required to compress the image, through the process of compression of digital image data using Discrete Wavelet Transform algorithms using Haar filter, and Contourlet. Using Laplace and Directional Filter, Curvelet transformation using FDCT- Wrapping Technology .The performance of the algorithms used in the proposed research is also evaluated using a Ratio Compression (RC) scale, As well as the Peak signal to noise ratio (PSNR) scale, the mean sequence error (MSE) scale, the signal to noise ratio (SNR) scale, and finally, the Normalization correlation (NC) scale. Correspondence between the original image and the recovered image after compression, in order to choose the best algorithm that achieves the best compression ratio of the image and maintains the parameters of the recovered image based on the standards (MSE, PSNR, SNR, COR and CR) used with the three algorithms, and the results showed that the Curvelet transformation algorithm achieved : best compression ratio, but at the expense of image quality.