A depth estimation algorithm with a single image.

This paper explains the use of a sharpening filter to calculate the depth of an object from a blurred image of it. It presents a technique which is independent of edge orientation. The technique is based on the assumption that a defocused image of an object is the convolution of a sharp image of the same object with a two-dimensional Gaussian function whose spread parameter (SP) is related to the object depth. A sharp image of an object is obtained from a defocused image of the same object by applying sharpening filters. The defocused and sharp images of the object are used to calculate the SP which is then related to the object depth. The paper gives experimental results which show the feasibility of employing sharpening filters for depth computation.

Depth from automatic defocusing.

This paper presents a depth recovery method that gives the depth of any scene from its defocused images. The method combines depth from defocusing and depth from automatic focusing techniques. Blur information in defocused images is utilised to measure depth in a way similar to determining depth from automatic focusing but without searching for sharp images of objects. The proposed method does not need special scene illumination and involves only a single camera. Therefore, there are no correspondence, occlusion and intrusive emissions problems. The paper gives experimental results which demonstrate the accuracy of the method.