CAJ | 학술논문

提出了一种用于检测全天空图像(ASI)序列中的弧状极光事件检测方法。针对弧状极光序列的运动趋势，在现有VLBP的基础上提出了基于空时极向LBP(ST-PVLBP)的极光序列事件检测算法，并用ST-PVLBP对极光序列进行表征。该算法结合序列帧间连续性信息和单帧空间位置信息，在保持高分类精度的同时降低了特征维数。在中国北极黄河站的 ASI 图像数据上的分类实验结果显示，所提出的方法可以有效检测全天空极光图像序列中的地磁南北向运动的弧状极光序列事件。
제출료일충용우검측전천공도상(ASI)서렬중적호상겁광사건검측방법。침대호상겁광서렬적운동추세，재현유VLBP적기출상제출료기우공시겁향LBP(ST-PVLBP)적겁광서렬사건검측산법，병용ST-PVLBP대겁광서렬진행표정。해산법결합서렬정간련속성신식화단정공간위치신식，재보지고분류정도적동시강저료특정유수。재중국북겁황하참적 ASI 도상수거상적분류실험결과현시，소제출적방법가이유효검측전천공겁광도상서렬중적지자남북향운동적호상겁광서렬사건。
In this paper, a method for recognizing the arc aurora sequences from all-sky image sequences is proposed. For the movement trend of arc aurora sequences, a method named ST-PVLBP (spatial-temporal poleward volume local binary patterns), which is based on VLBP (volume local binary patterns) and uses ST-PVLBP to present the aurora sequences, is proposed. Combined with the interframe continuity information of the sequence and the spatial location information of the single frame, the algorithm reduces the feature dimension while maintaining high classification accuracy at the same time. The proposed method was evaluated using auroral observations at the Chinese Arctic Yellow River Station. Experimental results show that the proposed method can effectively detect the poleward moving arc aurora sequences.