A simple PSF parameters estimation method for the de-blurring of linear motion blurred images using wiener filter in OpenCV

Motion blur is one of the most common causes of image degradation which is caused by the relative motion between the camera and the scene during the exposure time. Because of motion blur degradation, some important image data may be lost and that will seriously affect in various imaging application fields, such as medical imaging, remote sensing and face recognition. To restore a motion blurred image to its near original form, the motion parameters such as its blur length and blur angle must be properly estimated. In this paper, new algorithms for motion parameters estimation are proposed using a single degraded image. For motion direction estimation, this algorithm applies a method of direct detection to the DFT central spectral line which is very simple. For motion length estimation two methods are proposed, one by the detection of the DFT central spectral line width, and another one by the detection without rotation of the DFT spectrum. The experimental results showed that the proposed methods provide a simple solution to image deblurring for their simplicity of direct detection nature and provide faster execution time in deblurring.