文献类型：期刊文献

英文题名：Kernel based color estimation for night vision imagery

作者：Gu, Xiaojing[1];Sun, Shaoyuan[2];Fang, Jian'an[2];Zhou, Peng[3]

机构：[1]E China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]Donghua Univ, Coll Informat Sci & Technol, Dept Automat, Shanghai, Peoples R China;[3]Hong Kong Polytech Univ, Dept Comp, Hunghom, Hong Kong, Peoples R China

年份：2012

卷号：285

期号：7

起止页码：1697

外文期刊名：OPTICS COMMUNICATIONS

收录：;EI(收录号：20120514725845);WOS:【SSCI(收录号:WOS:000301035400013)，SCI-EXPANDED(收录号:WOS:000301035400013)】；

基金：This work is supported by the National Natural Science Foundation of China (Nos. 61072090 and 60874113).

语种：英文

外文关键词：Night vision; Color enhancement; Nonlinear method

摘要：Displaying night vision (NV) imagery with colors can largely improve observer's performance of scene recognition and situational awareness comparing to the conventional monochrome representation. However, estimating colors for single-band NV imagery has two challenges: deriving an appropriate color mapping model and extracting sufficient image features required by the model. To address these, a kernel based regression model and a set of multi-scale image features are used here. The proposed method can automatically render single-band NV imagery with natural colors, even when it has abnormal luminance distribution and lacks identifiable details. (C) 2011 Elsevier B.V. All rights reserved.