A Modified Image Processing Method for Deblurring Based on GAN Networks

In computer vision literature, it is really a challenging issue about removing the images blur resulted from camera shake. As the existing image deblurring methods do not apply to the image degraded by partial motion blur, and the existing partial blur detection approaches only used low -level blur features to measure the blurry degree of an image, the blur regions extracted via these methods usually have misclassification. To solve the imaging deblurring problem, we propose an image deblurring method based on Generative Adversarial Network (GAN) architecture using dual path connection. In comparison with the traditional image deblurring algorithm, this model can avoid the dependence on apriori-knowledge of blurred image. Experimental results show that the proposed method significantly outperforms other state-of-art algorithms on image deblurring.