Performance of stack filters and vector detection in image restoration

Kenneth E. Barner; Gonzalo R. Arce; Jean H. Lin

doi:10.1117/12.19611

1 July 1990 Performance of stack filters and vector detection in image restoration

Kenneth E. Barner, Gonzalo R. Arce, Jean H. Lin

Proceedings Volume 1247, Nonlinear Image Processing; (1990) https://doi.org/10.1117/12.19611
Event: Electronic Imaging: Advanced Devices and Systems, 1990, Santa Clara, CA, United States

Abstract

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.

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Kenneth E. Barner, Gonzalo R. Arce, and Jean H. Lin "Performance of stack filters and vector detection in image restoration", Proc. SPIE 1247, Nonlinear Image Processing, (1 July 1990); https://doi.org/10.1117/12.19611

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KEYWORDS

Digital filtering

Image restoration

Sensors

Interference (communication)

Image processing

Nonlinear image processing

Quantization

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