We perform an analysis of the TRACE telescope blur from EUV images. The blur pattern is discussed in terms of the telescope point spread function (PSF) for the 171 Å filter. The analysis performed consists of two steps. First an initial shape for the PSF core is determined directly from TRACE EUV images. Second, the blind deconvolution approach is used for obtaining the final PSF shape. The PSF...

In this paper we present a general framework of the state space approach for blind deconvolution. First, we review the current state of the art of blind deconvolution using statespace models, then give a new insight into blind deconvolution in the state-space framework. The cost functions for blind deconvolution are discussed and adaptive learning algorithms for updating external parameters are...

Thermocouples are one of the most popular devices for temperature measurement in many mechatronic implementations. However, large wire diameters are required to withstand harsh environments and consequently the sensor bandwidth is reduced. This paper describes a novel algorithmic compensation technique based on blind deconvolution to address this loss of high frequency signal components using t...

The ‘Bussgang’ is one of the most known blind deconvolution algorithms. It requires the prior knowledge of the source statistics as well as the deconvolution noise characteristics. In this paper we present a first attempt for making the algorithm ‘more blind’ by replacing the original Bayesian estimator with a flexible parametric function whose parameters adapt through time. To assess the effec...

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A novel approach is presented in this paper to improve images which are altered by atmospheric turbulence. Two new algorithms are presented based on two combinations of a blind deconvolution block, an elastic registration block and a temporal filter block. The algorithms are tested on real images acquired in the desert in New Mexico by the NATO RTG40 group.

An approach to multi-channel blind deconvolution is developed, which uses an adaptive filter that performs blind source separation in the Fourier space. The approach keeps (during the learning process) the same permutation and provides appropriate scaling of components for all frequency bins in the frequency space. Experiments verify a proper blind deconvolution of convolution mixtures of sources.

OF THESIS Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Science Optical Science and Engineering The University of New Mexico Albuquerque, New Mexico May, 2007