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14 April 2021 Image translation to enhance IR2VIS image registration
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Abstract
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.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ran Zhang, Junchi Bin, Zheng Liu, and Erik Blasch "Image translation to enhance IR2VIS image registration", Proc. SPIE 11733, Geospatial Informatics XI, 117330A (14 April 2021); https://doi.org/10.1117/12.2588034
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