Image comparison based on semivariogram and its application

This paper describes the use of semivariogram as a parameter for image comparison which is a commonly used method in content-based image retrieval. The authors first review various applications of spatial statistics to image and signal processing, and recent literature of image comparison, with the emphasis to global image structure description and distance-based image retrieval techniques. The difficulty arising in this field is the definition of image similarity. A new parameter based on semivariogram is putted forward by the authors. Bearing in mind that semivariogram is a parameter not only describes the global structure of a data set but also describes the local continuity of that data set, it is shown in the paper that semivariogram is suitable for global image comparison, and can be used to reveal local features of the image as well. Based on this property, a new index for image similarity is constructed and a practical program using it is developed. By applying the approach to a practical problem, the results show that this approach has the following merits: (a) high sensitivity to structure differences of an image. (b) low computational complexity, and (c) high robustness to lightening conditions.

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