DCT-based Local Motion Blur Detection

One of the frequently encountered problems in photography is the appearance of motion blurring effect due to either object movement or camera motion associated with the speed of the camera (shutter speed) when pictures are taken. This Paper presents a novel but simple method of detecting unwanted motion blur effects that appear local within an arbitrary area on a digital image. The proposed method uses various size block-based discrete cosine transform (DCT) calculations on the distorted image. The outcome of this detection are then subsequently used to improve the quality of the image by means of pixel correlation based deblurring method applied to the specific area identified by our motion blur detector. Subjective experiment to evaluate the quality of the resulting enhanced image is then conducted and objective evaluations using several published image quality metrics are also computed. Experimental results show that the quality of the enhanced images produced by the chosen deblurring method is better when local motion blur detection is employed than those without blur detection. Out of various block sizes used in the experiment, block size of 32 x 32 pixels produce better perceived quality.