[1]卢清秀,任成森,叶文权. 稀疏表达的夜间图像采集分辨率无关处理技术[J].计算机技术与发展,2017,27(10):11-15.
　LU Qing-xiu,REN Cheng-sen,YE Wen-quan. An Independent Processing Technology of Night Image Acquisition Resolution Based on Sparse Representation[J].,2017,27(10):11-15.
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 稀疏表达的夜间图像采集分辨率无关处理技术()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年10期
页码:
11-15
栏目:
智能、算法、系统工程
出版日期:
2017-10-10

文章信息/Info

Title:
 An Independent Processing Technology of Night Image Acquisition Resolution Based on Sparse Representation
文章编号:
1673-629X（2017)10-0011-05
作者:
 卢清秀; 任成森; 叶文权
 广东工业大学华立学院
Author(s):
 LU Qing-xiu; REN Cheng-sen; YE Wen-quan
关键词:
 ; 稀疏表达; 夜间图像; 图像采集; 分辨率; 三维重建
Keywords:
 ; sparse representation; night image; image acquisition; resolution; 3D reconstruction
分类号:
TP391
文献标志码:
A
摘要:
 在图像采集和三维重建中,需要进行图像分辨率无关处理,降低光照和环境因素给分辨率带来的影响,因此提出一种基于稀疏表达的夜间图像采集分辨率无关处理技术.首先对采集的夜间图像进行小波降噪处理,对夜间图像的阴影区域和亮度区域进行曲线分割.在夜间光照的多重色差条件下,用标准化稀疏先验的正则化表达方法进行图像均衡锁光处理,采用图像像素均匀遍历方法进行图像子块连续遍历,实现夜间采集图像的阴影偏差补偿,实现夜间图像采集的分辨率无关处理,解决图像分辨率带来的图像重构问题.仿真结果表明,采用该方法进行夜间图像采集分辨率无关处理,有效提高了图像的成像质量和可分辨度,峰值信噪比和计算开销的参量指标优于传统方法.
Abstract:
 In the image acquisition and 3D reconstruction,independent image resolution processing is needed to reduce the influence of il-lumination and environmental factors to the resolution. Therefore,an independent processing technology of night image acquisition resolu-tion is proposed based on the sparse expression. First the acquisition of night image is in wavelet denoising,conducting the curve segmen-tation of the shadow region and brightness region for night image. In the conditions of multiple color at night,the expression method of regularization of standardized sparse prior is used for the image equalization lock light processing,and image pixel traversal method for continuous uniform traversal of image blocks,realizing the shadow deviation compensation for acquisition image at night and independent resolution processing of that,solving the problem of image reconstruction caused by the resolution. The simulation results show that it can improve the imaging quality and resolution and the its peak signal-to-noise ratio and computing cost parameters are better than the tradi-tional method.

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更新日期/Last Update: 2017-11-23