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Journal Science Intensive Technologies №5 for 2013 г.
Article in number:
Statistical analysis of multidimensional image sequences
Authors:
K.K. Vasil-ev, V.R. Krasheninnikov, A.G. Tashlinskii
Abstract:
In a number of applied problems images can be represented in the form of random fields (RF) specified on multidimensional integer-valued grids. Several RF models are proposed. For presentation of RF with specified correlation properties autoregressive and wave models are proposed. Tensor RF model is suitable for images frames sequence description. In many applications there exists a problem of detection of anomalies which may appear on a regular multidimensional frame of images sequence. At Gaussian approximation of a posteriori distributions four forms of decision rule statistics have been obtained on the basis of which optimal algorithms of detection of lengthy anomalies with known and unknown characteristics on separate images and their sequences and on multispectral images have been developed and their effectiveness is determined. A number of recurrent algorithms of optimal and close to it quasioptimal filtering of grid images has been developed and their effectiveness has been determined. Image processing methods have been applied for speech signals and other quasi-periodic signals filtering by means of their transform into specific images. Image interframe geometric deformations (IGD) estimation is used when solving a wide range of problems. Investigations in this field were carried out in the following directions: synthesis of images sequence IGD parameters estimation quasioptimal non-identification procedures; analysis of accuracy of procedures at a finite number of estimation iterations; procedures optimization using a priori information about images; solving of applied problems of images and signals parameters estimation.
Pages: 5-11
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