摘要
针对采集的无序图像存在图像信息冗余、模糊,不能满足特征检测、目标识别、三维重建等技术质量要求的问题,基于图像质量约束,提出一种无序图像关键帧提取方法。采用不预设K-均值的聚簇算法对无序图像进行自动聚簇。根据相似距离从每簇中提取出离聚簇中心最近的一帧作为关键帧。运用二次模糊处理算法对提取的关键帧进行无参考图像质量评价,其评价值若满足质量要求则保留,否则返回原来的簇中重新进行关键帧的提取与评价,直到提取的关键帧满足质量要求为止。实验结果表明,该方法能较好地滤除冗余图像,提取出满足质量要求的关键帧。
For the random images,there are problems of redundant and blur image information,which cannot meet the technical requirements in terms of feature detection,target recognition and 3 D reconstruction,based on image quality constraint,this paper proposes a disordered image key frame extraction method. The clustering algorithm without presetting K-means is used for automatic clustering of disordered images. According to the similar distance,the frame,being closest to the clustering center from each clustering,are extracted as the key one. The quadratic blur processing algorithm is adopted to evaluate the extracted key frames for non-reference image quality. If the evaluation values are in accordance with quality requirements,the frames will be reserved. Otherwise, returns to the original cluster,extracts and evaluates the key frame again until the extracted frames meet the quality requirements. Experimental results show that the proposed method can filter out redundant images and extract the key frames satisfying the quality requirements.
出处
《计算机工程》
CAS
CSCD
北大核心
2017年第11期210-215,共6页
Computer Engineering
基金
国家自然科学基金(61561005
61271445)
广西科技攻关计划项目(桂科攻1598008-1)
关键词
无序图像
三维重建
关键帧提取
聚簇算法
二次模糊
disordered image
3D reconstruction
key frame extraction
clustering algorithm
quadratic blur
