Implementation and analysis of wavelet image decomposition and SPIHT algorithm

Many compression and coding algorithms for image compression based on different techniques have been developed and implemented to achieve certain standards and meet the required criteria but wavelet transform is the latest. Wavelet transform has the natural ability to give few coefficients as compared to other transforms, which carry the actual energy of the signal and image and hence offer comparatively more compression. Many wavelets have been designed and developed to perform this task. Wavelet decomposition has the ability to be applied down to many levels depending on the size of the image, which gives more and more compression. Now, in addition to wavelet transform different coding techniques like EZW, EBCOT and SPIHT for coefficients have been developed to give more compression and reduce the bit rate. This paper describes the wavelet decomposition to certain levels along with the SPIHT coding technique application to that level and their comparison in term of time taken which is machine dependent and image quality in terms of peak signal to noise ratio.