Traditionally, Markov models have not been successfully used for compression of signal data other than binary image data. Due to the fact that exact substring matches in non-binar...
We derive a six parameter system to estimate and compensate the effects of camera motion - zoom, pan, tilt and swing. As compared to other existing methods, this model describes m...
Yap-Peng Tan, Sanjeev R. Kulkarni, Peter J. Ramadg...
A real-world computer vision module must deal with a wide variety of environmental parameters. Object recognition, one of the major tasks of this vision module, typically requires...
In recent work, we have shown that morphological openings and closings can be viewed as consistent MAP estimators of morphologically smooth binary image signals immersed in i.i.d....
Nikolaos Sidiropoulos, John S. Baras, Carlos Alber...
A 3D super-resolution algorithm is proposed below, based on a probabilistic interpretation of the ndimensional version of Papoulis' generalized sampling theorem. The algorith...
Hassan Shekarforoush, Marc Berthod, Josiane Zerubi...
While Bayesian methods can significantly improve the quality of tomographic reconstructions, they require the solution of large iterative optimization problems. Recent results ind...
Magnetic resonance spectroscopic imaging (MRSI) is a type of MRI in which both spatial and spectral information are gathered. Unfortunately, the time required to acquire a high-re...
A structure for implementing lapped transforms with time-varying block sizes is presented which allows full orthogonality of the transient transforms. The formulation is based on ...
In this paper, we address the problem of color image restoration. Here, we model the image as a Markov Random Field (MRF) and propose a restoration algorithm in a multiresolution ...
P. K. Nanda, K. Sunil Kumar, S. Ghokale, Uday B. D...