Information Meausures of Scale-space Based on Visual Characters
基于视觉特征的尺度空间信息量度量

The basic idea behind a multi-scale representation is to embed the original image into such a one-parameter family of derived images,which become more and more smooth and simple.The simplification means the loss of details and information.It is important to measure the information of an image at a given scale and the loss between scales.Based on the vision theory and intuition of image processing,the paper proposed seven principles: nonnegativity,causality,Geometric invariability and so on.Sporring and Weickert have proposed a method of information measures.But Sporring's measure can not satisfy the principles proposed in this paper.This paper presented a new information measure based on the Marr's Vision Theory.In Gaussian Scale space of one dimension,we used the number of the first-class and the second-class of points as the information measure.Use the theory of Gaussian scale space,this paper has proofed that the new measure method satisfies the principles proposed.Then we extend the method in two dimensions directly.Experimental results proof its reliability.So this is a good choice of information meausures of scale-space based on the visual characters.