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国土资源遥感  2019, Vol. 31 Issue (2): 51-58    DOI: 10.6046/gtzyyg.2019.02.08
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
视频卫星影像的Bayer插值重建
吴佳奇1,2,汪韬阳2(),彭雨芬3,张过4
1.辽宁工程技术大学测绘与地理科学学院,阜新 123000
2.武汉大学遥感信息工程学院,武汉 430079
3.湖北地信科技集团股份有限公司,武汉 430074
4.武汉大学测绘遥感信息工程国家重点实验室,武汉 430079
Bayer interpolation for video satellite images
Jiaqi WU1,2,Taoyang WANG2(),Yufen PENG3,Guo ZHANG4
1.School of Geomatics, Liaoning Technical University, Fuxin 123000, China
2.School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
3.Hubei Geomatics Technology Group Stock Co., Ltd., Wuhan 430074, China
4.State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
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摘要 

视频卫星在成像过程中一般采用Bayer模板,地面处理时需要通过Bayer插值处理才可恢复全彩色的影像。针对视频卫星影像Bayer插值重建中容易出现拉链、噪点和边缘伪彩色等问题,提出一种改进的基于亮度、色度信号重建的滤波方法。首先,通过24张标准柯达影像训练得出Bayer插值重建的带通滤波器; 其次,通过带通滤波器提取色度信号,并根据Bayer模型获取初始的重建结果; 然后,在绿色空间中,利用梯度信息进行均值区域判断,并在均值和非均值区域中分别进行边缘方向插值和色差域中值滤波更新,有效减少均值区域的插值拉链和噪点现象; 最后,在新的色差域中进行红光、蓝光波段的导向插值和中值滤波更新,进一步提升插值精度。采用吉林一号01星和03星的4幅视频影像数据验证本文方法的有效性,结果表明与2种经典的Bayer插值方法相比,提出的改进方法在定性和定量评价上均最优,影像边缘更加锐利、清晰,无明显噪点和伪彩色现象,可用于卫星视频数据的后续处理和应用。

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吴佳奇
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彭雨芬
张过
关键词 视频卫星Bayer插值Bayer模型中值滤波边缘方向    
Abstract

Video satellite capture color video data are obtained by using the single CMOS sensor with color filter array (CFA) Bayer pattern. To obtain the full color image sequences, researchers should perform the processing of Bayer image interpolation. Aimed at the interpolation of satellite video Bayer image, the authors propose a improved method based on the signal filter reconstruction of luminance and chrominance. Firstly, band-pass filters are used for extracting luminance and chrominance signal. And the initial reconstruction result can be obtained according to the Bayer spatial model. Moreover, median filtering in non-smooth region and edge direction interpolation in the smooth region are applied to the G-B or G-R difference band for updating the green band. In the end, the red band and blue band are also updated in the new G-B or G-R difference band. To verify the feasibility of the proposed method, the authors tested 4 video Bayer image of Jilin-1 01 and 03 and compared the obtained results with two classic methods. The experimental results show that method designed by the authors has the best comprehensive performance both in subjective evaluation and objective evaluation. The reconstructed image quality is good and has no obvious noise and pseudo-color effects; in addition, the edge is sharp and clear. The method can be used for satellite video further processing and application.

Key wordsvideo satellite    Bayer interpolation    Bayer model    median filter    edge direction
收稿日期: 2018-11-12      出版日期: 2019-05-23
ZTFLH:  TP391  
基金资助:国家重点研发计划项目“长时间序列气象卫星历史数据地理精定位技术研究”(2018YFB0504900-05);国家自然科学基金项目“高分卫星视频运动目标检测与轨迹提取方法研究”(91538106);“弱交会条件下顾及同轨约束关系的卫星影像区域网平差方法研究”共同资助(41501503)
通讯作者: 汪韬阳     E-mail: wangtaoyang@whu.edu.cn
作者简介: 吴佳奇(1985-),男,博士研究生,主要从事遥感影像信息提取与识别研究。Email: jiaqiwu@126.com。
引用本文:   
吴佳奇,汪韬阳,彭雨芬,张过. 视频卫星影像的Bayer插值重建[J]. 国土资源遥感, 2019, 31(2): 51-58.
Jiaqi WU,Taoyang WANG,Yufen PENG,Guo ZHANG. Bayer interpolation for video satellite images. Remote Sensing for Land & Resources, 2019, 31(2): 51-58.
链接本文:  
http://www.gtzyyg.com/CN/10.6046/gtzyyg.2019.02.08      或      http://www.gtzyyg.com/CN/Y2019/V31/I2/51
Fig.1  Bayer模板
Fig.2  3个滤波器的三维频率响应
Fig.3  Bayer插值模板
Fig.4  方法流程
参数 视频01星 视频03星
轨道高度/km 650 535
轨道倾角/(°) 98(太阳同步) 97.5左右(太阳同步)
侧摆能力/(°) ±45 ±45
连续拍摄时长/s 120 120
成像模式 凝视和半凝视 凝视、半凝视、夜视和推扫
空间分辨率/m 1.13 <1
灰度量化/bits 8 8
Tab.1  吉林一号视频卫星01星和03星参数对比
Fig.5  Bayer插值重建结果
Fig.6  实验影像ROI
Tab.2  不同方法重建细节对比
影像 模糊比 噪声比
TSD方法 LSLCD方法 本文方法 TSD方法 LSLCD方法 本文方法
01星农田 0.904 5 0.938 0 0.907 7 0.400 8 0.397 4 0.407 7
01星林地 0.915 4 0.936 0 0.911 3 0.416 9 0.421 4 0.412 6
03星屋顶 0.986 7 0.989 4 0.986 2 0.418 4 0.421 3 0.422 3
03星机动车 0.939 8 0.950 0 0.912 2 0.391 2 0.389 5 0.391 0
平均值 0.936 6 0.953 4 0.929 3 0.406 8 0.407 4 0.408 4
Tab.3  Bayer插值重建的模糊比和噪声比对比
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