Abstract
Intensity histograms have been used extensively for recognition and for retrieval of images and video from visual databases. Intensity histograms of images at different individual resolutions have also been used for indexing. They suffer, however, from the inability to encode spatial image information. Spatial information can be incorporated into histograms simply by taking histograms of an image at multiple resolutions together to form a multiresolution histogram. Multiresolution histograms can also be computed, stored, and matched efficiently. The authors analyze and quantify the relation and sensitivity of the multiresolution histogram to spatial image information as well as to properties of shapes and textures in an image. They verify the analytical results experimentally and demonstrate the ability of multiresolution histograms to discriminate between images, as well as their robustness to noise.
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