Blur Invariants and Projection Operators
| Autor: | Tomáš Suk, Jan Flusser, Barbara Zitová, Jiří Boldyš |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Class (set theory)
business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Function (mathematics) Image (mathematics) Convolution Computer Science::Computer Vision and Pattern Recognition Canonical form Computer vision Artificial intelligence business Projection (set theory) Fourier domain Mathematics |
| Zdroj: | Computer Graphics and Imaging / 798: Signal Processing, Pattern Recognition and Applications. |
| DOI: | 10.2316/p.2013.798-018 |
| Popis: | In this paper, we introduce a new theory of blur invariants. Blur invariants are image features which preserve their values if the image is convolved with a point-spread function (PSF) of a certain class. We present the invariants to convolution with an arbitrary N-fold symmetric PSF, defined in Fourier domain by means of projection operators. We introduce a notion of a primordial image as a canonical form of all blur-equivalent images. We illustrate by experiments the invariance and recognition power of the new features. Potential applications of this method are wherever one wants to recognize blurred images. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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