Two new methods are presented for recovering the focused image of an object from only two blurred images recorded with different camera parameter settings.The camera parameters include lens position, focal length, and aperture diameter.First a blur parameter is estimated using one of our two recently proposed depth-fromdefocus methods.Then one of the two blurred images is deconvolved to recover the focused image.The first method is based on a recently proposed Spatial Domain Convolution/Deconvolution Transform.This method requires only the knowledge of of the camera's point spread function (PSF).It does not require information about the actual form of the camera's PSF.The second method, in contrast to the first, requires full knowledge of the form of the PSF.As part of the second method, we present a calibration procedure for estimating the camera's PSF for different values of the blur parameter .In the second method, the focused image is obtained through deconvolution in the Fourier Domain using the Wiener filter.For both methods, results of experiments on actual defocused images recorded by a CCD camera are given.The first method requires much less computation than the second method.The first method gives satisfactory results for up to medium levels of blur and the second method gives good results for up to relatively high levels of blur.

Two new methods are presented for recovering the focused image of an object from only two blurred images recorded with different camera parameter settings. First a blur parameter /spl sigma/ is estimated using one of our two recently proposed depth-from-defocus methods. Then one of the two blurred images is deconvolved to recover the focused image. The first method requires only the knowledge of /spl sigma/ of the camera's point spread function (PSF). It is based on a new spatial domain convolution/deconvolution transform. The second method requires full knowledge of the form of the PSF and is estimated using step edges. The focused image is obtained through deconvolution in the Fourier Domain using the Wiener filter. For both methods, results of experiments on actual defocused images recorded by a CCD camera are presented. The first method requires less computation and gives satisfactory results for up to medium levels of blur. The second method gives good results for up to relatively high levels of blur.>

The application of a new spatial-domain convolution/deconvolution transform (S transform) for determining the distance of objects using image defocus is described. The method, known as STMAP, involves simple local operations on only two images taken with different aperture diameters and can be easily implemented in parallel. Both images can be arbitrarily blurred, and neither of them needs to be a focused image taken with a pin-hole camera. STMAP is implemented on an actual camera system named the Stonybrook Passive Autofocusing and Ranging Camera System (SPARCS). Experimental results on real-world planar objects are presented. The results indicate that STMAP is useful in practical applications. The utility of the method is demonstrated for rapid autofocusing of electronic cameras. STMAP is computationally more efficient than other depth-from-focus methods. The results are comparable to a Fourier-transform-based approach.>