Efficient depth blurring with occlusion handling

We present a novel algorithm for enhancing an image or video frame with depth of field. The algorithm deals with occlusive blurring effects as occur in real cameras and can handle a variation in blur which is continuous up to blur level quantization granularity, with asymptotic complexity O(N log² N) in terms of time and memory for an N-pixel image, irrespective of the complexity of the variation in blur. The proposed algorithm is a postfiltering approach which, unlike prior algorithms, does not suffer from intensity leakage. Experimental results show the algorithm to be 3 to 4 times faster than an existing algorithm, which had the same asymptotic complexity.