The goal of deconvolution is to recover an image x from its convolution with a known blurring function. This is equivalent to inverting the linear system y = Hx. In this paper we ...
Graph cut algorithms (i.e., min s-t cuts) [3][10][15] are useful in many computer vision applications. In this paper we develop a formulation that allows the addition of side cons...
Reconstructing a 3-D scene from more than one camera is a classical problem in computer vision. One of the major sources of difficulty is the fact that not all scene elements are v...
Vladimir Kolmogorov, Ramin Zabih, Steven J. Gortle...
The geometric features of images, such as edges, are difficult to represent. When a redundant transform is used for their extraction, the compression challenge is even more dif...
—This paper addresses the problem of self-validated labeling of Markov random fields (MRFs), namely to optimize an MRF with unknown number of labels. We present graduated graph c...