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ROI and NROI Based Medical Image Compression using MSPIHT and Hybrid DWT with DCT

Author(s):

Mr. Tarun Das Manikpuri , Shri Shankaracharya Technical Campus,Shri Shankaracharya group of Institution(FET) Bhilai,C.G.; Mr. Chandrashekhar Kamargaonkar, Shri Shankaracharya Technical Campus,Shri Shankaracharya group of Institution(FET) Bhilai,C.G.

Keywords:

Modified Set Partitioning in Hierarchical Trees (MSPIHT), Transform Coding, Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), ROI, NROI, PSNR, CR. Structure Similarity Index (SSIM)

Abstract

This paper is intended to provide such medical image compression method which provides good peak signal to noise ratio (PSNR) for diagnosis important area also known as clinically region of interest (ROI) and a good compression ratio (CR) for non-region of interest (NROI) that is background of the medical image. The proposed method is used taking into account the salience of medical images. With the improvement of digital imaging the space required by the images gradually increases. The medical images occupy large space in storage device. High transmission time and high resolution proves the need for images compression. The main task in medical imaging is coding and transmission of medical images by preserving the clinically important information with reduction in storage space with the help of compression. Nowadays medical image compression is an important area of research which aims at producing algorithms that reduce file size and at the same time maintain relevant diagnostic information. This paper concentrates on using such methods which preserves the CROI with loss less method and other then that region like edges and background known as NROI with lossy method. In this paper the lossless modified set partitioning in hierarchical trees (MSPIHT) algorithm in ROI part, which is gives more appropriate and robust image transmission, and the hybrid of lossy methods DCT with DWT is used in NROI part of image.

Other Details

Paper ID: IJSRDV5I41165
Published in: Volume : 5, Issue : 4
Publication Date: 01/07/2017
Page(s): 1073-1076

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