Near Infrared Star Centroid Detection by Area Analysis of Multi-Scale Super Pixel Saliency Fusion Map  

作　　者：Xiaohu Yuan Shaojun Guo Chunwen Li Bin Lu Shuli Lou 

机构地区：[1]the Department of Automation, Tsinghua University [2]the National Innovation Institute of Defense Technology [3]Naval Aeronautical University [4]Yantai University

出　　处：《Tsinghua Science and Technology》2019年第3期291-300,共10页清华大学学报（自然科学版（英文版）

基　　金：supported in part by the National Natural Science Foundation of China (No. 61303192)

摘　　要：The centroid location of a near infrared star always deviates from the real center due to the effects of surrounding radiation. To determine a more accurate center of a near infrared star, this paper proposes a method to detect the star's saliency area and calculate the star's centroid via the pixels only in this area, which can greatly decrease the effect of the radiation. During saliency area detection, we calculated the boundary connectivity and gray similarity of every pixel to estimate how likely it was to be a background pixel. Aiming to simplify and speed up the calculation process, we divided the near infrared starry sky image into super pixel maps at multi-scale by Simple Linear Iterative Clustering(SLIC). Second, we detected the saliency map for every super pixel map of the image. Finally, we fused the saliency maps according to a weighted coefficient that is determined by the least square method. For the images used in our experiment, we set the multi-scale super pixel numbers to 100, 150,and 200. The results show that our method can obtain an offset variance of less than 0.27 for the center coordinates compared to the labelled centers.The centroid location of a near infrared star always deviates from the real center due to the effects of surrounding radiation. To determine a more accurate center of a near infrared star, this paper proposes a method to detect the star's saliency area and calculate the star's centroid via the pixels only in this area, which can greatly decrease the effect of the radiation. During saliency area detection, we calculated the boundary connectivity and gray similarity of every pixel to estimate how likely it was to be a background pixel. Aiming to simplify and speed up the calculation process, we divided the near infrared starry sky image into super pixel maps at multi-scale by Simple Linear Iterative Clustering(SLIC). Second, we detected the saliency map for every super pixel map of the image. Finally, we fused the saliency maps according to a weighted coefficient that is determined by the least square method. For the images used in our experiment, we set the multi-scale super pixel numbers to 100, 150,and 200. The results show that our method can obtain an offset variance of less than 0.27 for the center coordinates compared to the labelled centers.

关 键 词：near INFRARED starry STAR SALIENCY Simple Linear ITERATIVE Clustering (SLIC) 

分 类 号：N[自然科学总论]