A multivalued image wavelet representation based on multiscale fundamental forms

Authors:
P. Scheunders
Affiliations:
Dept. of Phys., Antwerp Univ.
Venue:
IEEE Transactions on Image Processing
Year:
2002

Citing 0
Cited 5

Feature space and metric measures for fusing multisensor images

International Journal of Remote Sensing
Edge-preserving smoothing using a similarity measure in adaptive geodesic neighbourhoods

Pattern Recognition
Image segmentation based on GrabCut framework integrating multiscale nonlinear structure tensor

IEEE Transactions on Image Processing
Iris recognition against counterfeit attack using gradient based fusion of multi-spectral images

IWBRS'05 Proceedings of the 2005 international conference on Advances in Biometric Person Authentication
A Wavelet Perspective on Variational Perceptually-Inspired Color Enhancement

International Journal of Computer Vision

Quantified Score

Hi-index	0.01

Visualization

Abstract

A new wavelet representation for multivalued images is presented. The idea for this representation is based on the first fundamental form that provides a local measure for the contrast of a multivalued image. In this paper, this concept is extended toward multiscale fundamental forms using the dyadic wavelet transform of Mallat (1992). The multiscale fundamental forms provide a local measure for the contrast of a multivalued image at different scales. The representation allows for a multiscale edge description of multivalued images. A variety of applications is presented, including multispectral image fusion, color image enhancement and multivalued image noise filtering. In an experimental section, the presented techniques are compared to single valued and/or single scale algorithms that were previously described in the literature. The techniques, based on the new representation are demonstrated to outperform the others.