Abstract
Large calibrated datasets of 'random' natural images have recently become available. These make possible precise and intensive statistical studies of the local nature of images. We report results ranging from the simplest single pixel intensity to joint distribution of 3 Haar wavelet responses. Some of these statistics shed light on old issues such as the near scale-invariance of image statistics and some are entirely new. We fit mathematical models to some of the statistics and explain others in terms of local image features.
Keywords
WaveletHaar waveletComputer scienceArtificial intelligencePixelRangingStatisticsNatural (archaeology)Image (mathematics)Pattern recognition (psychology)Wavelet transformComputer visionMathematicsDiscrete wavelet transformGeography
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Publication Info
- Year
- 2003
- Type
- article
- Pages
- 541-547
- Citations
- 508
- Access
- Closed
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Cite This
Jinggang Huang,
D. Mumford
(2003).
Statistics of natural images and models.
, 541-547.
https://doi.org/10.1109/cvpr.1999.786990
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- DOI
- 10.1109/cvpr.1999.786990