Image Compression for Telemedicine using New Wavelets and Modified EZW

With the invent of better signal processing operations unveiled by the research community of both communication and signal processing, the Telemedicine is becoming more and more prominent all over the world. Communicating the data captured from the patient to the clinicians in non-recognizable seconds of time is crucial in many cases so as to take a right decision at right time. Then the processing of the data sent to clinicians is the second part of telemedicine where extensive processing capabilities are required. In this paper, the first part of telemedicine is answered by devising diversified schemes using wavelet and modification of standard coding scheme embedded zero tree wavelet (EZW). First, coding by EZW and Set partitioning in Hierarchical tree (SPIHT) was implemented. Then, new wavelets and their lifting versions are designed. Finally, two variations of standard EZW scheme were proposed. The simulation results suggest that the techniques presented in this paper provide better compression performance at different levels of compression ratio (CR) and peak signal to noise ratio (PSNR). In addition to CR and PSNR, bit error rate and output bandwidths are calculated.