Detection and Classification of Invariant Blurs
| Autor: | Rachel Mabanag Chong, Toshihisa Tanaka |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
business.industry
Applied Mathematics ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Feature selection Pattern recognition Computer Graphics and Computer-Aided Design Maxima and minima Signal Processing Preprocessor Computer vision Artificial intelligence Deconvolution Electrical and Electronic Engineering Invariant (mathematics) business Mathematics |
| Zdroj: | IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences. :3313-3320 |
| ISSN: | 1745-1337 0916-8508 |
| DOI: | 10.1587/transfun.e92.a.3313 |
| Popis: | A new algorithm for simultaneously detecting and identifying invariant blurs is proposed. This is mainly based on the behavior of extrema values in an image. It is computationally simple and fast thereby making it suitable for preprocessing especially in practical imaging applications. Benefits of employing this method includes the elimination of unnecessary processes since unblurred images will be separated from the blurred ones which require deconvolution. Additionally, it can improve reconstruction performance by proper identification of blur type so that a more effective blur specific deconvolution algorithm can be applied. Experimental results on natural images and its synthetically blurred versions show the characteristics and validity of the proposed method. Furthermore, it can be observed that feature selection makes the method more efficient and effective. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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