红外技术, 2015, 37 (12): 1041, 网络出版: 2016-01-19  

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
作者单位
1 东华大学信息科学与技术学院, 上海 201620
2 东华大学数字化纺织服装技术教育部工程研究中心, 上海 201620
3 华东理工大学信息科学与工程学院, 上海 200237
摘要
为了将红外图像中所包含的信息更加友好、直观地呈现给用户, 改善用户对于红外图像的理解效果, 针对车载红外图像的特点, 提出了一种基于随机森林分类器和超像素分割算法相结合的车载红外图像彩色化算法。首先对原图的各个像素点进行特征提取, 然后训练随机森林分类器, 使它能够对待测试图像的各个像素点进行正确的分类。再使用超像素分割与直方图统计相结合的方法对分类结果图像进行优化。最后将优化后的分类结果图像转换到 HSV色彩空间进行对应的色彩传递。通过实验证明该方法能够在很好的对红外图像进行彩色化处理的同时, 保证色彩传递的正确性和实时性。
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.

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, 37(12): 1041. SHEN Zhen-yi, SUN Shao-yuan, HOU Jun-jie, ZHAO Hai-tao. The Vehicle Infrared Image Colorization Algorithm Based on Random Forest and Superpixel Segmentation[J]. Infrared Technology, 2015, 37(12): 1041.

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