• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.1
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• pp.43-48
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• 2012

This paper proposes a practical linear recursive robust motion deblurring filter using the inertial sensor measurements for strapdown image seekers. The angular rate information obtained from the gyro mounted on the missile is used to define the PSF(point spread function). Since the gyro output contains a unknown but bounded bias error. the motion blur image model can be expressed as the linear uncertain system. In consequence, the motion deblurring problem can be cast into the robust Kalman filtering which provides reliable state estimates even in the presence of the parametric uncertainty due to the gyro bias. Through the computer simulations using the actual IR scenes, it is verified that the proposed algorithm guarantees the robust motion deblurring performance.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.27-33
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• 2009

We propose an efficient method for single image motion deblurring using edge prediction. Previous methods for motion deblurring from a single image have been based on total variation or natural image statistics. In contrast, our method predicts sharp edges by applying bilateral and shock filters and manipulating image gradients directly, and estimates motion blur using the predicted sharp edges. Sharp edge prediction makes our method possible to deblur efficiently with less computation. Results show that our method can effectively and efficiently restore images degraded by large complex motion blur.