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Image processing via simulated quantum dynamics. (English) Zbl 1365.94053
Summary: We apply simulated quantum evolution to image processing, and examine its practicality in the context of image denoising. More specifically, in our approach image processing consists of three stages: First, a digitized gray-scale image is represented as a quantum variable – typically, a density matrix. Second, the quantum variable is evolved via the Markovian master equation in Lindblad form. Third, the quantum variable is back-converted into an image. Numerical experiments indicate remarkable denoising results are obtained in this way for a suitable choice of flow parameters. To our knowledge the proposed image processing technique is conceptually new.
MSC:
94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
60G35 Signal detection and filtering (aspects of stochastic processes)
68U10 Computing methodologies for image processing
81S22 Open systems, reduced dynamics, master equations, decoherence
93E11 Filtering in stochastic control theory
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