COMPRESSIVE SENSING BASED IMAGE RECONSTRUCTION
Journal Title: World Journal of Engineering Research and Technology - Year 2017, Vol 3, Issue 3
Abstract
Compressive sensing is a technique of image acquisition and reconstruction from a relatively fewer measurements than what the Nyquist theorem suggests; the sampling rate must be greater than twice the highest frequency in the signal for fidelity of image reconstruction. Compressive sensing is applicable when the signals under consideration are sparse. Two-dimensional discrete wavelet transform is applied for sparse representation of an image in this thesis. When sparsity is more, the performance of compressive sensing image reconstruction algorithm will be better. The sparse level of low frequency sub bands and high frequency sub bands are different. Two different compressive sensing measurement matrixes and recovery algorithms are used for the low-frequency sub bands and high-frequency sub bands for better results. Medical field especially in MRI scanning, compressive sensing can be utilized for less scanning time, thus benefits patients. The reconstructed image will be better in both PSNR and visual quality.
Authors and Affiliations
Sherin C. Abraham
Keywords
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