2D Image Compression Using Wavelet Compression Technique by Analysis

Compressing an image is significantly different than compressing raw binary data. Of course, general purpose compression programs can be used to compress images, but the result is less than optimal. The compression is achieved by many algorithms like Haar, EZW, JPEG2000 and SPIHT [4] and we can get some good results but more efficient algorithm is required which is necessary to improve the PSNR value of the reconstructed image. This paper discusses important features of wavelet functions and filters used in sub band coding to convert image into wavelet coefficients in MATLAB. Image quality is measured objectively using peak signal to noise ratio (PSNR). The effect of different parameters is studied on different wavelet functions. Results provide a good reference for application designers of wavelet based coder. The quality of the compressed images has been evaluated using some factors like Compression Ratio (CR), Peak Signal to Noise Ratio (PSNR), Mean Opinion Score (MOS), Picture Quality Scale (PQS).