Images similarity estimation by processing compressed data
A method is proposed to evaluate the similarity of images compressed by a given digital wavelet transform. The method allows for comparing lossless- or lossy-compressed images. Two features that describe the image structural content, namely edge point locations and edge density, are computed directly from multiscale data. The distance between two images is computed in one- or two-dimensional space, depending on the image type and the choice of features selected for processing. The method facilitates content-based image querying and automatic database retrieval. Additionally, images can be sorted and appropriately indexed with respect to such characteristics as smoothness, texture direction, repetition period and the average number of edge points in spatial period.
Electrical and Computer Engineering | Engineering | Signal Processing
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Deng, S. L.
Images similarity estimation by processing compressed data.
Image and Vision Computing, 19(7),