Image and Signal Processing Methods

Efficient simultaneous image deconvolution and upsampling algorithm for low-resolution microwave sounder data

[+] Author Affiliations
Jing Qin, Wotao Yin

University of California, Department of Mathematics, Los Angeles, California 90095, United States

Igor Yanovsky

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, United States

University of California, Joint Institute for Regional Earth System Science and Engineering, Los Angeles, California 90095, United States

J. Appl. Remote Sens. 9(1), 095035 (Dec 24, 2015). doi:10.1117/1.JRS.9.095035
History: Received May 29, 2015; Accepted November 16, 2015
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Abstract.  Microwave imaging has been widely used in the prediction and tracking of hurricanes, typhoons, and tropical storms. Due to the limitations of sensors, the acquired remote sensing data are usually blurry and have relatively low resolution, which calls for the development of fast algorithms for deblurring and enhancing the resolution. We propose an efficient algorithm for simultaneous image deconvolution and upsampling for low-resolution microwave hurricane data. Our model involves convolution, downsampling, and the total variation regularization. After reformulating the model, we are able to apply the alternating direction method of multipliers and obtain three subproblems, each of which has a closed-form solution. We also extend the framework to the multichannel case with the multichannel total variation regularization. A variety of numerical experiments on synthetic and real Advanced Microwave Sounding Unit and Microwave Humidity Sounder data were conducted. The results demonstrate the outstanding performance of the proposed method.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Jing Qin ; Igor Yanovsky and Wotao Yin
"Efficient simultaneous image deconvolution and upsampling algorithm for low-resolution microwave sounder data", J. Appl. Remote Sens. 9(1), 095035 (Dec 24, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.095035


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