N. B Chopade
A.A. Ghatol
M.T. Kolte
Abstract
The necessity in image compression continuously grows during the lastdecade. The statistics shows thatten billion images are getting added every year. Now a day's medical imaging has become an active research area. Medical images includes, X-ray images, MRI, ECG, EMG, EEG plots. The collection of medical images form huge analog image data. In an uncompressed form, these images require huge memory storage and very large bandwidth for their transmission. With the advent of new technology, processor speed, memory density, storage & transmission of medical image data becomes an expensive matter. One of the most powerful and perspective approach in this area is image compression using discrete wavelet transform. This technique includes transform ofan image, quantization ofwavelet coefficients and coding. This paper presents wavelet basedcoding algorithm Set Partitioning In Hierarchical Trees to encode & decode the image data. It uses recursive set partitioning procedure to sortsubsets of wavelet coefficient by maximum magnitude with respect to threshold. Because of low complexity & simplicity, this algorithm has fast encoding and decoding which makes it very efficient in medical image compression, storage retention and transmission. The numerical results obtained using MATLAB shows that the output image has high value ofPeak Signalto Noise Ratio with good Compression Ratio for low bit rate
Keywords- Discrete Wavelet Transform (DWT), Set Partitioning in Hierarchical Trees (SPIHT), Peak-Signal to Noise Ratio (PSNR) andCompression Ratio (CR).