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Stochastic Geometry for Image Analysis
Stochastic Geometry for Image Analysis.part1.rar
(15 MB, 下载次数: 90 )
Stochastic Geometry for Image Analysis.part2.rar
(6.37 MB, 下载次数: 71 )
Mathematical techniques for modeling random phenomena have found a natural application in the feld of image analysis. An image is itself a noisy signal, due to the characteristics of the imaging sensor and the conditions of image acquisition or transmission. Noise reduction techniques, low-pass fltering, and Kalman flters, all of which were initially developed in signal theory, have been easily generalized to apply to the case of two-dimensional (2D) images, and thereafter to higher dimensions. Nevertheless, the random phenomena within an image are not solely the result of noise. The content of the image itself can be regarded as the product of a random process. |
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