Depth from Defocus using Radial Basis Function Networks

In range finding, the depth from defocus (DFD) is a simple and effective method. We use the DFD method to analyze the defocused images to obtain depth information using Gaussian blurred function. In order to find the range of objects, a sigma value of the Gaussian function due to edges out of focus is necessary. Since the sigma value of the Gaussian function depicts on the intensity of images grabbed by imaging devices, we employ an approximate method, the radial basis function networks (RBFN), to approach the sigma value directly in the spatial domain. The RBFN regularizes the center position and the sigma value of the Gaussian function to fit the profile of the defocused image by three layers of neural networks based on the radial basis function. It has accurate ranging results with less than 8% of the root mean square error in sigma value approaching and 5% of the relative error in ranging, imaging system ranges from 220 mm to 355 mm and focuses at 400 mm.