抽象的

Adaptive Motion Detection for Image Deblurring in RTS Controller

Sandeep Mishra, Abanikanta Pattanayak, Radhanath Patra, Subhrajit Pradhan, Subodh Panda

An Adaptive method for Image Deblurring is presented here. Processing of image data collected from both surveillance camera and on road traffic control motor vehicle camera is a big issue because often the objects are in motion and sometimes both the objects and camera are not steady. This leads to Blurring of the image and further image processing is not possible due to the degradation of received image. So Image Deblurring techniques are applied before enhancement or further processing. But it needs proper data for Deblurring like the frequency characteristics (Point Spread Function (PSF)) and Noise characteristics (Noise-to-Signal Power Ratio(NSR)). The method presented here gives the above information along with the motion information. The information about motion detection is very important because in the Deblurring process the noise estimation cannot be done without knowing actual pixels of the sensor noise present in the image. So to get a deblurred image with proper noise reduction that can be further processed in the RTS (Road Traffic & Safety) controller required information are provided sequentially according to the motion detection and Deblurring algorithm. This method uses some good Deblurring methods like Blind Deconvolution and Regularization filtering along with proper motion detections and characteristics estimations to get an image close to the true image which is sufficient for further processing.