Image Compression Using Haar Wavelet Transform

Abstract

Compressing an image is significantly different than compressing raw binary data. General purpose compression programs can be used to compress images, but the result is less than optimal. This is because images have certain statistical properties which can be exploited by encoders specifically designed for them. Also, some of the finer details in the image can be sacrificed for the sake of saving a little more bandwidth or storage space. This also means that lossy compression techniques can be used in this area. The discrete wavelet is essentially sub band's coding system and sub band coders have been quite successful in speech and image compression. In this paper we have implemented HAAR Wavelet Transform. The results in terms of PSNR(Peak Signal Noise Ratio) and MSE (Mean Square Error)show that the Haar transformation can be used for image compression. The quantization is done by dividing the image matrix into blocks and taking mean of the pixel in the given block. It is clear that DWT has potential application in the compression problem and the use of Haar transform is ideally suited.