| 摘要 |
An image digest based search approach allows images within an image repository related to a query image to be located despite cropping, rotating, localized changes in image content, compression formats and/or an unlimited variety of other distortions. In particular, the approach allows potential distortion types to be characterized and to be fitted to an exponential family of equations matched to a Bregman distance. Image digests matched to the identified distortion types may then be generated for stored images using the matched Bregman distances, thereby allowing searches to be conducted of the image repository that explicitly account for the statistical nature of distortions on the image. Processing, associated with characterizing image noise, generating matched Bregman distances, and generating image digests for images within an image repository based on a wide range of distortion types and processing parameters may be performed offline and stored for later use, thereby improving search response times.
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