Images Reconstruction Algorithm Based on DCT and Compressive Sensing

Authors

  • Xinyue Wang
  • Dequan Zhou School of Jiyang, Zhejiang A & F University, zhuji

Keywords:

Compressive Sensing, Images Reconstruction, Orthogonal Matching Pursuitï¼› DCT transform

Abstract

In order to improve the quality of reconstructed images, a method combining DCT algorithm and compressive sensing theory is presented. Firstly, the DCT transform is applied to change an image to sparse domain, and then the high-frequency coefficients of the sparse domain is measured by using a Gaussian random, finally, the algorithm of OMP is used to reconstruct the image.Compared with the direct compressive sensing algorithm, simulation results demonstrated that the presented algorithm improved the quality of the reconstructed image significantly. For the same number of sampled data sets, the PSNR of the presented algorithm was improved about 5 dB.

References

Richard G. Baraniuk, “Compressive Sensing â€, IEEE Signal Processing Magazine, vol. 24, no. 4, pp. 118-121, 2007.

D. Donoho, “Compressed sensingâ€, IEEE Trans. Inform. Theory, vol. 52, no. 4, pp.1289–1306, 2006.

Xie Chengjun, Zhang Tieshan, “Research on Compressed Sensing Theory-Based Image Reconstructionâ€, Computer Applications and Software (Chinese), vol.29, no.4, pp.49-52, 2012.

Cen Yi-gang, Chen Xiao-fang, & et al., “Compressed sensing based on the single layer wavelet transform for image processingâ€, Journal on Communications (Chinese), vol.31, no. 8, pp.52-55, 2010.

Pan Rong, Liu Yu, Hou Zheng-Xin, Wang Shao-Chu, “Image Coding and Reconstruction via Compressed Sensing Based on Partial DCT Coefficientsâ€, Acta Automatica Sinica (Chinese), vol.37, no.6, pp.674-681, 2011.

Lian Qiu-Sheng, Xiao ying., “Image Compressed Sensing Algorithm Based on Wavelet Tree Structure and Iterative Shrinkageâ€, Journal of Electronics & Information Technology (Chinese), Vol.33, no.4, pp.967-971,2011.

Joel A., Tropp, Anna C. Gilbert, “Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit â€, IEEE Transactions on Information Theory, Vol.53, no.12, pp. 4655-4666, 2007.

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Published

2013-10-14

How to Cite

Wang, X., & Zhou, D. (2013). Images Reconstruction Algorithm Based on DCT and Compressive Sensing. Asian Journal of Computer and Information Systems, 1(3). Retrieved from https://ajouronline.com/index.php/AJCIS/article/view/424