Open AccessHigh Speed Data Exchange Algorithm in Telemedicine with Wavelet based on 4D Medical Image Compression
Author(s) -
Samreen Fatima
Publication year - 2021
Publication title -
international journal of engineering and management research
Language(s) - English
Resource type - Journals
eISSN - 2394-6962
pISSN - 2250-0758
DOI - 10.31033/ijemr.11.4.6
Subject(s) - peak signal to noise ratio , artificial intelligence , computer science , discrete wavelet transform , pixel , wavelet , algorithm , computer vision , mean squared error , image compression , set partitioning in hierarchical trees , wavelet transform , data compression , pattern recognition (psychology) , image (mathematics) , mathematics , image processing , statistics
Existing Medical imaging techniques such as fMRI, positron emission tomography (PET), dynamic 3D ultrasound and dynamic computerized tomography yield large amounts of four-dimensional sets. 4D medical data sets are the series of volumetric images netted in time, large in size and demand a great of assets for storage and transmission. Here, in this paper, we present a method wherein 3D image is taken and Discrete Wavelet Transform(DWT) and Dual-Tree Complex Wavelet Transform(DTCWT) techniques are applied separately on it and the image is split into sub-bands. The encoding and decoding are done using 3D-SPIHT, at different bit per pixels(bpp). The reconstructed image is synthesized using Inverse DWT technique. The quality of the compressed image has been evaluated using some factors such as Mean Square Error(MSE) and Peak-Signal to Noise Ratio (PSNR).