Blurred Image Restoration Anddepth Detection With Cepstrum Method

Automation industry developed rapidly in recent years, in the field of automation, AOI(Automatic Optic Inspection) as a new technology is developing rapidly, too. Automated optical inspection equipment can detect the defects and displacement information of the desired compound more quickly in automated production for subsequent adjustment. But in the current application of the above, there will be some problems, such as if the camera is relatively cheap, then there due to camera movement caused by excessive captured image may be blurred,In the field of automated production, visual measurement technique s have been widely used,Defocus measurement technique has been widely used because of low cost and accurate measurement.This thesis first presents a real-time restoration method for linear local motion-blur images. The proposed approach is to firstly divide such an image into many sub-images and then detect the blurred sub-image by the gradient distribution and the cepstrum maximum. For a blurred sub-image, the blur direction and blur length are estimated in order to calculate the parameters of the point spread function(PSF). The Richardson-Lucy deconvolution algorithm and Wiener filtering are employed to restore this blurred sub-image, we found that the effect of the method of our paper obvious by comparison with other algorithms.Issues relating to the calculation of blur parameters can also come out of another popular research- ranging monocular vision. There is a method called depth from defocus method in monocular vision, the principle is to calculate the blur parameters offspring into the corresponding formula based on the size of the captured image blurred region to determine the point spread object distance. This paper proposes two methods to calculate the object distance. The first method is first extracted the defocus blur parameters based on cepstrum, and then substituting the parameters into equation to get the object distance. The second method is to obtain two different images by adjusting the distance between the lens and the imaging surface to get the blur parameters to calculate the distance calculation,this method requires the distance between the lens and the CCD of the camera can be fine-tuning. Both the two methods are based on the cepstral domain, we can choose for different application environments.