24 October 2017 Texture aware learning-based image fusion method for fixed focal-length cameras
Author Affiliations +
Proceedings Volume 10462, AOPC 2017: Optical Sensing and Imaging Technology and Applications; 104624V (2017) https://doi.org/10.1117/12.2285610
Event: Applied Optics and Photonics China (AOPC2017), 2017, Beijing, China
Abstract
This paper aims to develop a novel approach of image fusion for an asymmetrical camera system when multiple images are acquired with cameras which have large differences in focal lengths but similar sensor size with an overlapping field of view. The fused image usually becomes perceptually unpleasant because the high-frequency components of a wideview image will be quite inadequate comparing to the tele-view images. Four steps are consisted in the proposed work: (i) image upscaling of the wide-view image, (ii) texture identification on the upscaled image, (iii) the performance evaluation of image upscaling, and (iv) the image inpainting for the high-frequency components of the wide-view image. The field of view of tele-view camera is set to be 4 times smaller than the wide-view camera in spatial angle in the experiment. The experiment result illustrates that the proposed algorithm brings significantly perceptual improvement to the wide-view image.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Haoyu Ma, Haoyu Ma, Zhihai Xu, Zhihai Xu, Huajun Feng, Huajun Feng, Qi Li, Qi Li, Yueting Chen, Yueting Chen, Jiazi Huang, Jiazi Huang, } "Texture aware learning-based image fusion method for fixed focal-length cameras", Proc. SPIE 10462, AOPC 2017: Optical Sensing and Imaging Technology and Applications, 104624V (24 October 2017); doi: 10.1117/12.2285610; https://doi.org/10.1117/12.2285610
PROCEEDINGS
6 PAGES


SHARE
Back to Top