Improved Content-Based Watermarking Using Scale-Invariant Feature Points

Na Li, Edwin R. Hancock, Xiaoshi Zheng, Lin Han

Abstract: For most HVS(Human Visual System) perceptual models, the JND(Just Noticeable Difference) values in highly-textured image regions have little difference with those in edge areas. This is not consistent with the characteristics of human vision. In this paper, an improved method is introduced to give a better content-based perceptual mask than traditional ones using the arrangement of scale-invariant feature points. It could decrease the JND values in edge areas of those traditional masks so that they have an obvious difference with values in highly textured areas. Experimental results show the advantages of this improved approach visually, and the enhancement of the invisibility of watermarks.