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Enhanced Performance Metrics for Blind Image Restoration

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Advances in Intelligent Computing (ICIC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3644))

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Abstract

Mean Squared Error (MSE) has been the performance metric in most performance appraisals up to date if not all. However, MSE is useful only if an original non degraded image is available in image restoration scenario. In blind image restoration, where no original image exists, MSE criterion can not be used. In this article we introduce a new concept of incorporating Human Visual System (HVS) into blind restoration of degraded images. Since the image quality is subjective in nature, human observers can differently interpret the same iterative restoration results. This research also attempts to address this problem by quantifying some of the evaluation criteria with significant improvement in the consistency of the judgment of the final result. We have modified some image fidelity metrics such as MSE, Correlation Value and Laplacian Correlation Value metrics to be used in iterative blind restoration of blurred images. A detailed discussion and some experimental results pertaining to these issues are presented in this article.

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© 2005 Springer-Verlag Berlin Heidelberg

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Premaratne, P., Safaei, F. (2005). Enhanced Performance Metrics for Blind Image Restoration. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538059_12

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  • DOI: https://doi.org/10.1007/11538059_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28226-6

  • Online ISBN: 978-3-540-31902-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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