24 August 2010 Image deblurring by motion estimation for remote sensing
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Abstract
The imagery resolution of imaging systems for remote sensing is often limited by image degradation resulting from unwanted motion disturbances of the platform during image exposures. Since the form of the platform vibration can be arbitrary, the lack of priori knowledge about the motion function (the PSF) suggests blind restoration approaches. A deblurring method which combines motion estimation and image deconvolution both for area-array and TDI remote sensing has been proposed in this paper. The image motion estimation is accomplished by an auxiliary high-speed detector and a sub-pixel correlation algorithm. The PSF is then reconstructed from estimated image motion vectors. Eventually, the clear image can be recovered by the Richardson-Lucy (RL) iterative deconvolution algorithm from the blurred image of the prime camera with the constructed PSF. The image deconvolution for the area-array detector is direct. While for the TDICCD detector, an integral distortion compensation step and a row-by-row deconvolution scheme are applied. Theoretical analyses and experimental results show that, the performance of the proposed concept is convincing. Blurred and distorted images can be properly recovered not only for visual observation, but also with significant objective evaluation increment.
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Yueting Chen, Yueting Chen, Jiagu Wu, Jiagu Wu, Zhihai Xu, Zhihai Xu, Qi Li, Qi Li, Huajun Feng, Huajun Feng, } "Image deblurring by motion estimation for remote sensing", Proc. SPIE 7810, Satellite Data Compression, Communications, and Processing VI, 78100U (24 August 2010); doi: 10.1117/12.859988; https://doi.org/10.1117/12.859988
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