학술논문

Distributed Compressive Sensing based Near Infrared and Visible Images Fusion for Face Recognition
Document Type
Article
Text
Author
Source
International Journal of Signal Processing, Image Processing and Pattern Recognition, 04/30/2016, Vol. 9, Issue 4, p. 281-292
Subject
distributed compressive sensing
information fusion
face recognition
joint sparse representation
Language
English
ISSN
2005-4254
Abstract
In this paper, we propose a novel face recognition method based on fusing the near infrared and visible images of face images with distributed compressive sensing. The near infrared image and visible image of one same subject constitute an ensemble. Both images in one ensemble share a common sparse component while each individual image has an innovation component. To better capture the complementary information of the ensemble, the distributed compressive sensing is used to obtain the common component and the innovation component of near infrared and visible image. The obtained common component contains the complementary information of near infrared and visible image effectively. So the sparse coefficients of the common component obtained by distributed compressive sensing can better capture the intrinsic structures of each image and therefore can obtain better performance than that of only using near infrared image or visible image. The experimental results on several benchmark datasets demonstrate the effectiveness of proposed method.