Infrared to Visible (IR2VIS) image registration suffers from the challenge of cross-modal feature extraction and matching. Conventional methods usually design the same keypoint detector for both Infrared (IR) and Visible (VIS) images. The VIS images are even converted to gray-scale images before the keypoint detection. IR and VIS gray-scale images have different properties which might not be applicable for the same feature detector. Therefore, this paper proposes an IR2VIS image registration method, namely, Image Translation for Image Enhanced Registration (ITIER). The IR images are first translated to realistic VIS images by Wavelet-Guided Generative Adversarial Network (WGGAN) for the convenience of cross-modal feature detection. Then the keypoint detection and matching and the homography transformation, which have been integrated into our ITIER, are conducted on the translated and original VIS images. Experimental results demonstrate that the IR2VIS image registration accuracy is greatly enhanced by the image-to-image translation procedure, which transfers IR images to realistic VIS images.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.