Super-resolution analysis of microwave image using WFIPOCS
Xue Wang, Jin Chu Wu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
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.