A Comprehensive Approach for Multi-channel Image Registration

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Abstract

We describe a general framework for multi-channel image registration. A new similarity measure for registering two multi-channel images, each with an arbitrary number of channels, is proposed. Results show that image registration performed based on different channels generates different results. In addition, we show that, when available, the inclusion of multi-channel data in the registration procedure helps produce more accurate results.