利用超分辨率红外视频增强目标检测和分类性能

C. Kwan, David Gribben, Bence Budavari
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引用次数: 3

摘要

远程红外视频,如国防系统信息分析中心(DSIAC)视频通常不具有高分辨率。近年来,视频超分辨率算法取得了重大进展。本文对超分辨率视频用于目标检测和分类的研究进行了综述。我们观察到,超分辨率视频可以显著提高检测和分类性能。例如,对于3000米范围的视频,我们能够将目标检测的平均精度从11%(无超分辨率)提高到44%(有4倍超分辨率),目标分类的总体精度从10%(无超分辨率)提高到44%(有2倍超分辨率)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Target Detection and Classification Performance Enhancement using Super-Resolution Infrared Videos
Long range infrared videos such as the Defense Systems Information Analysis Center (DSIAC) videos usually do not have high resolution. In recent years, there are significant advancement in video super-resolution algorithms. Here, we summarize our study on the use of super-resolution videos for target detection and classification. We observed that super-resolution videos can significantly improve the detection and classification performance. For example, for 3000 m range videos, we were able to improve the average precision of target detection from 11% (without super-resolution) to 44% (with 4x super-resolution) and the overall accuracy of target classification from 10% (without super-resolution) to 44% (with 2x superresolution).
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