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- W2801687130 abstract "As a powerful high resolution image modeling technique, compressive sensing (CS) has beensuccessfully applied in digital image processing and various image applications. This paper proposes a newmethod of efficient image reconstruction based on the Modified Frame Reconstruction Iterative ThresholdingAlgorithm (MFR ITA) developed under the compressed sensing (CS) domain by using total variation algorithm.The new framework is consisted of three phases. Firstly, the input images are processed by the multilookprocessing with their sparse coefficients using the Discrete Wavelet Transform (DWT) method. Secondly, themeasurements are obtained from sparse coefficient by using the proposed fusion method to achieve the balanceresolution of the pixels. Finally, the fast CS method based on the MFR ITA is proposed to reconstruct the highresolution image. In addition, the proposed method achieves good PNSR and SSIM values, and has shown fasterconvergence rate when performed the MFR ITA under the CS domain. Furthermore the graphical representationdemonstrated that the proposed method achieves better performance in terms of the SNR reconstruction and theprobability of successfully recovered signal, and also outperforms several other methods." @default.
- W2801687130 created "2018-05-17" @default.
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- W2801687130 date "2018-01-01" @default.
- W2801687130 modified "2023-09-23" @default.
- W2801687130 title "High Resolution Image Reconstruction Using Fast Compressed Sensing Based on Iterations" @default.
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