Abstract
This paper analyses wavelet filters and SPIHT encoding techniques in compression and decompression of medical images. Medical images acquired have uneven aspect ratio, region of interest decides the aspect ratio, and compression algorithm performance varies based on aspect ratio. This paper tries to offer a novel algorithm that preprocesses the input image with uniform aspect ratio prior to compression. Various DWT filters have been experimented with, to select the right type of filters for compressing and decompressing the images without sacrificing on the quality. Filter selection and its impact on compression ratio are also analyzed. Biorthogonal (Bior) and Daubechies (DB) achieve PSNR in the range of 45dB to 52dB for lossless compression. The modified algorithm proposed, normalizes the aspect ratio prior to compression using Discrete Wavelet Transform and SPIHT. The compressed bit stream is grouped into 128 bits and for each 128 bits hamming code is generated for error correction and detection. Various medical images have been used to validate the proposed compression algorithm and the developed algorithm is suitable for telemedicine applications.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
