Abstract
Image patches of different spatial frequencies are likely to have different perceptual significance as well as reflect different physical properties. Incorporating such concept is helpful to the development of more effective image retrieval techniques. In this paper, we introduce a method which separates an image into layers, each of which retains only pixels in areas with similar spatial frequency characteristics and uses simple low-level features to index the layers individually. The scheme associates indexing features with perceptual and physical significance thus implicitly incorporating high level knowledge into low level features. We present a computationally efficient implementation of the method, which enhances the power and at the same time retains the simplicity and elegance of basic color indexing. Experimental results are presented to demonstrate the effectiveness of the method.
Original language | English |
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Pages (from-to) | 102-113 |
Number of pages | 12 |
Journal | IEEE Transactions on Image Processing |
Volume | 12 |
Issue number | 1 |
DOIs | |
Publication status | Published - 1 Jan 2003 |
Keywords
- Color indexing
- Content-based image retrieval
- Human vision
- Signal analysis
ASJC Scopus subject areas
- Software
- General Medicine
- Computer Graphics and Computer-Aided Design