Based On Complex Path Of Motion Blurred Image Simulation And Research

Image-bluring is caused by the relative motion between the camera and the object during the exposure time. It is also called motion blur. In the military field, the camera installed before the missile warhead will take a image what is a composite blur image with rotation motion blur and linear motion blur before hit the target. This article mainly studies the simulation and restoration algorithms for the motion-blur image, the main work is given blow.1.This paper describes three linear motion blur restoration algorithms, first introduce the algorithm principle, then do recovery experiments and evaluate the quality, Contrast the differences between different methods. The results show that the inverse-filtering can recover the primitive image basically, but it is quite sensitive to the noise. The restoration quality of constrained least square method has some improvement,but it is still unable to eliminate the effective noise. The Wiener filtering may eliminate noise by chooses the appropriate parameter. Then this paper describes two rotation motion blur restoration algorithms:a restoration approach based on geometric coordinate transformations and a restoration approach base on deconvolution along blurring paths. The results show that when the rotation angle become more and more big. the quality of restoration is worse by the two methods, but the second method is better then the first method.2.This paper propose a complex path composite image motion blur with rotating and linear motion blur, take mathematical modeling to the blurred image using the physical meaning of exposure time, and then gives the method to blur image,which accumulate images divided into a number of exposure time image using imaging principle, and then averaging simulation blurred image. Finally, do the experiment and get the blur images under different parameters.3.This paper propose a method to restore the complex path motion blurred image based on Moore-Perrose Inverse. The algorithm have three steps:First calculation the pixels blur path, find all the blur set of pixels with the same PSF. Second using the Moore-Perrose Inverse transform restore image to find the solution of equations. Final take the pixels after restore to the original location and remove the hole points, then get the restoration image. And do recovery experiments to prove the algorithm feasibilitv.