Compressive Sensing Based Image Reconstruction

Compressive Sensing is novel technique where reconstruction of an image can be done with less number of samples than conventional Nyquist theorem suggests. The signal will pass through sensing matrix wavelet transformation to make the signal sparser enough which is a criterion for compressive sensin...

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Bibliographic Details
Published inFuture Internet Technologies and Trends Vol. 220; pp. 97 - 105
Main Authors Abraham, Sherin C., Pathak, Ketki, Patel, Jigna J.
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2018
Springer International Publishing
SeriesLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Subjects
Compressive sensing
DARC prediction
LZW encoder
Predictive coding
Sparsity
Wavelet transform
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Summary:Compressive Sensing is novel technique where reconstruction of an image can be done with less number of samples than conventional Nyquist theorem suggests. The signal will pass through sensing matrix wavelet transformation to make the signal sparser enough which is a criterion for compressive sensing. Different levels of wavelet decomposition are also analyzed in this paper. The performance further can be improved by using DARC prediction method. The prediction error signal transmitted through OFDM channel. The reconstructed image should be better in both PSNR and bandwidth. Medical field especially in MRI scanning, compressive sensing can be utilized for less scanning time.
ISBN:3319737112
9783319737119
ISSN:1867-8211
1867-822X
DOI:10.1007/978-3-319-73712-6_10