1 July 1990 Performance of stack filters and vector detection in image restoration
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Two techniques for image restoration are compared in this paper. One is a technique based on the theory of optimal adaptive stack filtering; the other is a recently developed vector detection approach to image restoration. The primary difference between these two techniques is that the optimal detection technique exploits multilevel a priori information, while the stack filter uses only single level information. Both approaches have very similar design constraints: (a) both rely on the existence of a training sequence for the image source in order to obtain optimal processing; (b) the underlying random fields need not be stationary and a direct computation of the statistics of the desired images is not required. Adaptive stack filters do, however, require a training set of the noise while the optimal detection approach only needs a multivariate parametric representation. The image restoration performance of these two methods is compared in a signal dependent noise environment characterizing imaging systems with speckle, film-grain, and Poisson shot noise. Comparisons are made using the Mean Absolute Error measure as well as a subjective measure.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenneth E. Barner, Gonzalo R. Arce, Jean H. Lin, "Performance of stack filters and vector detection in image restoration", Proc. SPIE 1247, Nonlinear Image Processing, (1 July 1990); doi: 10.1117/12.19611; https://doi.org/10.1117/12.19611

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