红外技术Issue(12)：1041-1046,6.
基于随机森林和超像素分割优化的车载红外图像彩色化算法
The Vehicle Infrared Image Colorization Algorithm Based on Random Forest and Superpixel Segmentation
摘要
Abstract
In order to improve the effect of the information contained in the infrared image which makes the infrared image much more friendly and intuitive to users. According to the characteristics of the vehicular infrared image, this paper proposes a vehicular infrared image colorization algorithm, which is combined of random forest classifier and superpixel segmentation algorithm. Firstly this method extracts the original characteristic of each pixel, and then trains the random forest classifier which can make sure that each test image classified correctly. Secondly it can use the combination of superpixel segmentation and histogram statistics to optimize the classification results. Finally it can convert the optimization of classification result images to HSV color space and do the corresponding color transfer. The experiments prove that this method can be very good in dealing with infrared image colorization, and at the same time, it can ensure the accuracy and timeliness of color transfer.关键词
车载红外图像/图像彩色化/随机森林/超像素分割Key words
vehicular infrared image/image colorization/random forest/superpixel segmentation分类
信息技术与安全科学引用本文复制引用
沈振一,孙韶媛,侯俊杰,赵海涛..基于随机森林和超像素分割优化的车载红外图像彩色化算法[J].红外技术,2015,(12):1041-1046,6.基金项目
国家自然科学基金资助项目，编号61072090，61205017，61375007。 （）
