A Video Deblurring Optimization Algorithm Based on Motion Detection

Abstract

Although the performance of image acquisition devices has been improved dramatically in recent years, especially in the resolution and clarity, defocusing and motion blur are still big problems. Upgrading the devices with the better hardware is one way to solve the problem, but the costs will usually increase disproportionately comparing with what we get. The appropriate image restoration algorithm could improve the clarity and the recognition rate of images significantly. However, the huge computation of those image restoration algorithms makes them unpractical. A new image restoration algorithm based on video target detection and an accelerating method using the Graphic Processing Units (GPU) parallel computing architecture are proposed, which makes it efficient enough to handle 720p high-definition (HD) video processing in real time and makes sure that only the interested blurred regions get restored and other parts of the image will not be impacted.