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 mutirresolution 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.

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: A. Lopez-Caloca, Boris Escalante-Ramírez
• Keywords: Gaussian Derivative Model, Hermite Transform, ICIP 2003, Image Fusion Schemes, Image Processing, Relevant Image Patterns, Transform Coefficient Domain