An optimized run-length based algorithm for sparse remote sensing image labeling

作     者：Shen-shen Luan Bo-wen Cheng Shuai Jiang Yu-hang Wu Zong-ling Li Ji-yang Yu Shen-shen Luan;Bo-wen Cheng;Shuai Jiang;Yu-hang Wu;Zong-ling Li;Ji-yang Yu

作者机构：Institute of Spacecraft System EngineeringHaidian DistrictBeijingChina 

出 版 物：《Defence Technology（防务技术）》 (Defence Technology)

年 卷 期：2022年第18卷第4期

页      面：663-677页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 081002[工学-信号与信息处理] 

主　　题：Connected-component labeling Label equivalence resolving Hardware implementation Equivalence matrix On-board processing 

摘      要：Labeling of the connected components is the key operation of the target recognition and segmentation in remote sensing *** conventional connected-component labeling(CCL) algorithms for ordinary optical images are considered time-consuming in processing the remote sensing images because of the larger size.A dynamic run-length based CCL algorithm(Dy RLC) is proposed in this paper for the large size,big granularity sparse remote sensing image,such as space debris images and ship *** addition,the equivalence matrix method is proposed to help design the pre-processing method to accelerate the equivalence labels *** result shows our algorithm outperforms 22.86% on execution time than the other algorithms in space debris image *** proposed algorithm also can be implemented on the field programming logical array(FPGA) to enable the realization of the real-time processing on-board.