Research Article
Compressive Sensing Based Image Reconstruction
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@INPROCEEDINGS{10.1007/978-3-319-73712-6_10, author={Sherin Abraham and Ketki Pathak and Jigna Patel}, title={Compressive Sensing Based Image Reconstruction}, proceedings={Future Internet Technologies and Trends. First International Conference, ICFITT 2017, Surat, India, August 31 - September 2, 2017, Proceedings}, proceedings_a={ICFITT}, year={2018}, month={2}, keywords={Compressive sensing Wavelet transform Sparsity DARC prediction Predictive coding LZW encoder}, doi={10.1007/978-3-319-73712-6_10} }- Sherin Abraham
Ketki Pathak
Jigna Patel
Year: 2018
Compressive Sensing Based Image Reconstruction
ICFITT
Springer
DOI: 10.1007/978-3-319-73712-6_10
Abstract
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.
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