13 March 2013 Super-resolution analysis of microwave image using WFIPOCS
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Abstract
Microwave images are always blurred and distorted. Super-resolution analysis is crucial in microwave image processing. In this paper, we propose the WFIPOCS algorithm, which represents the wavelet-based fractal interpolation incorporates the improved projection onto convex sets (IPOCS) technique. Firstly, we apply down sampling and wiener filtering to a low resolution (LR) microwave image. Then, the wavelet-based fractal interpolation is applied to preprocess the LR image. Finally, the IPOCS technique is applied to solve the problems arisen by interpolation and to approach a high resolution (HR) image. The experimental results indicate that the WFIPOCS algorithm improves spatial resolution of microwave images.
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Xue Wang, Xue Wang, Jin Wu, Jin Wu, } "Super-resolution analysis of microwave image using WFIPOCS", Proc. SPIE 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing, 87831L (13 March 2013); doi: 10.1117/12.2020949; https://doi.org/10.1117/12.2020949
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