Use of Linear Diffusion in Depth Estimation Based on Defocus Cue

Diffusion has been used extensively in computer vision. Most common applications of diffusion have been in low level vision problems like segmentation and edge detection. In this paper a novel application of the linear diffusion principle is made for the estimation of depth using the properties of the real aperture imaging system. The method uses two defocused images of a scene and the lens parameter setting as input and estimates the depth in the scene, and also generates the corresponding fully focused equivalent pin-hole image. The algorithm described here also brings out the equivalence of the two modalities, viz. depth from focus and depth from defocus for structure recovery.