Virtual focus and depth estimation from defocused video sequences
IEEE Transactions on Image Processing
Blind deblurring of foreground-background images
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Single image defocus map estimation using local contrast prior
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
View interpolation using defocused stereo images: a space-invariant filtering approach
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Blind and semi-blind deblurring of natural images
IEEE Transactions on Image Processing
Near-invariant blur for depth and 2D motion via time-varying light field analysis
ACM Transactions on Graphics (TOG)
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We present a novel filtering method for reconstructing an all-in-focus image or an arbitrarily focused image from two images that are focused differently. The method can arbitrarily manipulate the degree of blur of the objects using linear filters without segmentation. The filters are uniquely determined from a linear imaging model in the Fourier domain. An effective and accurate blur estimation method is developed. The simulation results show that the accuracy and computational time of the proposed method are improved compared with the previous iterative method and that the effects of blur estimation error on the quality of the reconstructed image are very small. The method performs well for real images acquired without visible artifacts.