We study the problem of uncertainty in the entries of the Kernel matrix, arising in SVM formulation. Using Chance Constraint Programming and a novel large deviation inequality we derive a formulation which is robust to such noise. The resulting formulation applies when the noise is Gaussian, or has finite support. The formulation in general is non-convex, but in several cases of interest it red...

We present a method to recover scenes deteriorated by superposition of transparent and semi-reflected contributions, as appear in reflections off windows. Separating the superimposed contributions from the images in which either contribution is in focus is based on mutual blurring and subtraction of the perturbing components. This procedure requires the defocus blur kernels to be known. The use...

Recent algorithms for exemplar-based single image super-resolution have shown impressive results, mainly due to well-chosen priors and recently also due to more accurate blur kernels. Some methods exploit clustering of patches, local gradients or some context information. However, to the best of our knowledge, there is no literature studying the benefits of using semantic information at the ima...

Noise filtering of images is essentially a smoothing process, and it is an issue that has been addressed for many years. The most commonly used low-pass filtering methods blur important image structures such as edges and lines, and thus reduce image contrast and damage image fidelity. This paper presents a structure adaptive anisotropic filtering technique with its application to processing mag...

We address the problem of space-variant image deblurring, where different parts of the image are blurred by different blur kernels. Assuming a region-wise space variant point spread function, we first solve the problem for the case of known blur kernels and known boundaries between the different blur regions in the image. We then generalize the method to the challenging case of unknown boundari...

Blind image deconvolution is an ill-posed problem since there exists infinite pairs of blur kernels and latent images. To obtain reasonable results this problem, most previous methods have emphasized the importance selecting salient edges for kernel estimation. In paper, a blind method based on explicit implicit selection proposed. Explicit edge achieved by using mutually guided filtering, whil...

Blur is a useful cue for depth. Natural images contain objects at a range of depths whose depth can be signaled by their perceived blur. Here, to evaluate the usefulness of blur as a depth cue, we estimate the number blur levels that observers can perceive simultaneously. To estimate this value, observers discriminated and classified dead leaves patterns that contained a controlled distribution...