An Efficient ROI Encoding Based on LSK and Fractal Image Compression

Telemedicine is one of the emerging fields in medicine which is characterized by transmitting medical data and images between different users. The medical images which are transmitted over the internet require huge bandwidth. Even images of single patient are found to be very huge in size due to resolution factor and number of images per diagnosis. So, there is an immense need for efficient compression techniques that can be used to compress these medical images. In medical images, only some of the regions are considered to be more important than the others (e.g., tumor in brain Magnetic Resonance Imaging (MRI)). This paper reviews the application of ROI coding in the field of telemedicine. The image coding is done using Wavelet Transform (WT) based on Listless Speck (LSK). The Region of Interest (ROI) is obtained from user interaction and coded with the user given resolution to get high Compression Ratio (CR). In our proposed method, instead of decompressing all the blocks, we decompress only the similar blocks based on the index valued stored on the stack. Thus, our proposed method efficiently compresses the medical image. The performance measure can be analyzed by using Peak Signal to Noise Ratio (PSNR). The execution time of the proposed method will be reduced when compare to the other existing methods. The experimental result shows that the application of ROI coding using LSK brings about high compression rate and quality ROI