Compression Ratio and Peak Signal to Noise Ratio in Grayscale Image Compression using Wavelet

Abstract

Computer technology to human needs that touch every aspect of life, ranging from household appliances to robots for the expedition in space. The development of Internet and multimedia technologies that grow exponentially, resulting in the amount of information managed by computer is necessary. This causes serious problems in storage and transmission image data. Therefore, should be considered a way to compress data so that the storage capacity required will be smaller. In this research wanted to know the influence of wavelet to the compression ratio and to the PSNR (Peak Signal to Noise Ratio). Then the compression ratio and PSNR results than would be obtained so that the optimal wavelet, which has a high compression ratio and PSNR. Wavelet is used Daubechies, Coiflet, and Symlet families. Test images used are 8-bit grayscale images of size 512x512. Wavelet which has the highest compression ratio in each family is Haar, Coiflet 1, and Symlet 2. While the wavelet which has the highest PSNR in each family is Haar, Coiflet 3, and Symlet 5. For wavelet which has a compression ratio and PSNR values are optimal for each family are Haar, Coiflet 3, and Symlet 5.