Selection of best wavelet basis for image compression at decomposition level 5

For image compression, the properties of wavelet transform like multiresolution representation, scalability, and progressive transmission plays a vital role. There is a significant quantity of information in audio, video and image signals that is irrelevant and need to be compressed. Image compression reduces the number of bits required to represent an image. The storage requirements or transmission time is, thus reduced when the information is communicated over a distance. In this paper, performance parameters like Compression Ratio (CR), Energy Ratio (ER), Mean Square Error (MSE) and Peak Signal- to- Noise Ratio (PSNR) are determined to find the best wavelet to compress the still image at decomposition level 5.