Image fusion with the Hermite transform

The Hermite transform is an image representation model that incorporates some important properties of visual perception such as the analysis through overlapping receptive fields and the Gaussian derivative model of early vision. It also allows the construction of pyramidal multiresolution analysis-synthesis schemes. We show how the Hermite transform can be used to build image fusion schemes that take advantage of the fact that Gaussian derivatives are good operators for the detection of relevant image patterns at different spatial scales. These patterns are later combined in the transform coefficient domain. Applications of this fusion algorithm are found in medical imagery and remote sensing, name.

[1]  Jean-Bernard Martens,et al.  The Hermite transform-theory , 1990, IEEE Trans. Acoust. Speech Signal Process..

[2]  Richard A. Young,et al.  Oh say, can you see? The physiology of vision , 1991, Electronic Imaging.

[3]  Andrew B. Watson,et al.  The cortex transform: rapid computation of simulated neural images , 1987 .

[4]  R. Young GAUSSIAN DERIVATIVE THEORY OF SPATIAL VISION: ANALYSIS OF CORTICAL CELL RECEPTIVE FIELD LINE-WEIGHTING PROFILES. , 1985 .

[5]  Jean-Bernard Martens,et al.  Local orientation analysis in images by means of the Hermite transform , 1997, IEEE Trans. Image Process..

[6]  E N WILLMER,et al.  The physiology of vision. , 1955, Annual review of physiology.

[7]  Jean-Bernard Martens The Hermite transform-applications , 1990, IEEE Trans. Acoust. Speech Signal Process..

[8]  Yehoshua Y. Zeevi,et al.  The Generalized Gabor Scheme of Image Representation in Biological and Machine Vision , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  R. E. Raab Gabor's Signal Expansion and Degrees of Freedom of a Signal , 1982 .

[10]  P. Camarillo-Sandoval,et al.  Adaptive multiplicative-noise reduction in SAR images with polynomial transforms , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

[11]  Christine Pohl,et al.  Multisensor image fusion in remote sensing: concepts, methods and applications , 1998 .

[12]  Frederick J. Kozub,et al.  Oh Say, Can You See? , 1991 .