TY - JOUR TI - Fusion Infrared and Visible Images Using Optimal Weights JO - Journal of Information Systems and Telecommunication (JIST) JA - Iranian Academic Center for Education,Culture and Research LA - en SN - 2322-1437 AU - Mehrnoush Gholampour AU - Hassan Farsi AU - Sajad Mohamadzadeh AD - Birjand AD - University of Birjand AD - University of Birjand Y1 - 2015 PY - 2015 VL _ 11 IS - 1 SP - 1 EP - 10 KW - Image fusion KW - Useful features KW - Infrared image KW - Vision image KW - weighted averaging DO - 10.7508/jist.2015.03.006 N2 - Image fusion is a process in which different images recorded by several sensors from one scene are combined to provide a final image with higher quality compared to each individual input image. In fact, combination of different images recorded by different sensors is one of image fusion methods. The fusion is performed based on maintaining useful features and reducing or removing useless features. The aim of fusion has to be clearly specified. In this paper we propose a new method which combines vision and infrared images by weighting average to provide better image quality. The weighting average is performed in gradient domain. The weight of each image depends on its useful features. Since these images are recorded in night vision, the useful features are related to clear scene details. For this reason, object detection is applied on the infrared image and considered as its weight. The vision image is also considered as a complementary of infrared image weight. The averaging is performed in gradient of input images, and final composed image is obtained by Gauss-Seidel method. The quality of resulted image by the proposed algorithm is compared to the obtained images by state-of-the-art algorithms using quantitative and qualitative measures. The obtained results show that the proposed algorithm provides better image quality. UR - http://rimag.ir/fa/Article/14881 L1 - http://rimag.ir/fa/Article/Download/14881 TY -JOURId - 14881