Restoration of space-variant blurred image based on motion-blurred target segmentation

In imaging on moving target, it is easy to get spacevariant blurred image. In order to recover the image and gain recognizable target, an approach to recover the space-variant blurred image is presented based on image segmentation. Because of motion blur's convolution process, the pixels of observed image's target and background will be displaced and piled up to produce two superposition regions. As a result, the neighboring pixels in the superposition regions will have similar grey level change. According to the pixel's motion-blur character, the target's blurred edge of superposition region could be detected. Canny operator can be recurred to detect the target edge which parallels the motion blur direction. Then in the segmentation process, the whole target image which has the character of integral convolution between motion blur and real target image can be obtained. At last, the target image is restored by deconvolution algorithms with adding zeros. The restoration result indicates that the approach can effectively solve the kind of problem of space-variant motion blurred image restoration.