视频卫星影像的Bayer插值重建
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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。
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.
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.
引文
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[3]吴佳奇,张过,汪韬阳,等.结合运动平滑约束与灰度特征的卫星视频点目标跟踪[J].测绘学报,2017,46(9):1135-1146.Wu J Q,Zhang G,Wang T Y,et al. Satellite video point-target tracking in combination with motion smoothness constraint and grayscale feature[J]. Acta Geodaetica et Cartographica Sinica,2017,46(9):1135-1146.
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[5] Blu T,Thévenaz P,Unser M. Linear interpolation revitalized[J].IEEE Transactions on Image Process,2004,13(5):710-719.
[6]徐少雄,张宇,陈长征,等.低复杂度Bayer图像色彩重建算法[J].液晶与显示,2016,31(2):179-184.Xu S X,Zhang Y,Chen C Z,et al. Low complexity demosaicing algorithm for Bayer pattern image[J]. Chinese Journal of Liquid Crystals and Displays,2016,31(2):179-184.
[7] Lukac R,Martin K,Plataniotis K N. Demosaicked image post-processing using local color ratios[J]. IEEE Transactions on Circuits and Systems for Video Technology,2004,14(6):914-920.
[8]赵亮,张宇烽,黄长宁.基于色差空间的低复杂度Bayer图像插值算法[J].航天返回与遥感,2016,37(3):128-138.Zhao L,Zhang Y F,Huang C N. A low complexity interpolation algorithm for Bayer image based on color difference space[J].Spacecraft Recovery and Remote Sensing,2016,37(3):128-138.
[9] Duran J,Buades A. Self-similarity and spectral correlation adaptive algorithm for color demosaicking[J]. IEEE Transactions on Image Process,2014,23(9):4031-4040.
[10] Gunturk B,Altunbasak Y,Mersereau R M. Color plane interpolation using alternating projections[J]. IEEE Transactions on Image Processing,2002,11(9):997-1013.
[11] Korneliussen J T,Hirakawa K. Camera processing with chromatic aberration[J]. IEEE Transactions on Image Processing,2014,23(10):4539-4552.
[12] Pekkucuksen I,Altunbasak Y. Multiscale gradients-based color filter array interpolation[J]. IEEE Transactions on Image Processing,2013,22(1):157-165.
[13] Sreegadha G S. Image interpolation based on multi scale gradients[J]. Procedia Computer Science,2016,85:713-724.
[14] Dubois E. Frequency-domain methods for demosaicking of Bayersampled color image[J]. IEEE Signal Processing Letters,2005,12(12):847-850.
[15] Jeon G,Dubois E. Demosaicking of noisy Bayer-sampled color images with least-squares luma-chroma demultiplexing and noise level estimation[J]. IEEE Transactions on Image Processing,2013,22(1):146-156.
[16] Su C Y. Low-complexity hybrid demosaicing for color filter arrays[J]. Journal of the Chinese Institute of Engineerings,2008,31(1):173-179.
[17]王红卫.贝尔图像插值与无损编码研究[D].太原:太原理工大学,2010.Wang H W. Reseach on Image Interpolation and Lossless Compression Based on Bayer Pattern[D]. Taiyuan:Taiyuan University of Technology,2010.
[18] Dubois E. Filter design for adaptive frequency-domain Bayer demosaicking[C]//IEEE International Conference on Image Processing. Atlanta:IEEE,2006:2705-2708.
[19] Choi M G,Jung J H,Jeon J W. No-reference image quality assessment using blur and noise[J]. International Journal of Computer Science and Engineering,2009,3(2):76-80.
[20] Aguilar M A,Saldaa M,Aguilar F J,et al. Comparing geometric and radiometric information from Geo Eye-1 and WorldView-2multispectral imagery[J]. European Journal of Remote Sensing,2014,47(1):717-738.
[2]张过.高分辨率视频卫星标准产品分级体系[M].北京:科学出版社,2017.Zhang G. High Resolution Video Satellite Standard Product Staging Hierarchy[M]. Beijing:Science Press,2017.
[3]吴佳奇,张过,汪韬阳,等.结合运动平滑约束与灰度特征的卫星视频点目标跟踪[J].测绘学报,2017,46(9):1135-1146.Wu J Q,Zhang G,Wang T Y,et al. Satellite video point-target tracking in combination with motion smoothness constraint and grayscale feature[J]. Acta Geodaetica et Cartographica Sinica,2017,46(9):1135-1146.
[4]袁益琴,何国金,江威,等.遥感视频卫星应用展望[J].国土资源遥感,2018,30(3):1-8. doi:10. 6046/gtzyyg. 2018. 03.01.Yuan Y Q,He G J,Jiang W,et al. Application of earth observation system of video satellite[J]. Remote Sensing for Land and Resources,2018,30(3):1-8. doi:10. 6046/gtzyyg. 2018. 03. 01.
[5] Blu T,Thévenaz P,Unser M. Linear interpolation revitalized[J].IEEE Transactions on Image Process,2004,13(5):710-719.
[6]徐少雄,张宇,陈长征,等.低复杂度Bayer图像色彩重建算法[J].液晶与显示,2016,31(2):179-184.Xu S X,Zhang Y,Chen C Z,et al. Low complexity demosaicing algorithm for Bayer pattern image[J]. Chinese Journal of Liquid Crystals and Displays,2016,31(2):179-184.
[7] Lukac R,Martin K,Plataniotis K N. Demosaicked image post-processing using local color ratios[J]. IEEE Transactions on Circuits and Systems for Video Technology,2004,14(6):914-920.
[8]赵亮,张宇烽,黄长宁.基于色差空间的低复杂度Bayer图像插值算法[J].航天返回与遥感,2016,37(3):128-138.Zhao L,Zhang Y F,Huang C N. A low complexity interpolation algorithm for Bayer image based on color difference space[J].Spacecraft Recovery and Remote Sensing,2016,37(3):128-138.
[9] Duran J,Buades A. Self-similarity and spectral correlation adaptive algorithm for color demosaicking[J]. IEEE Transactions on Image Process,2014,23(9):4031-4040.
[10] Gunturk B,Altunbasak Y,Mersereau R M. Color plane interpolation using alternating projections[J]. IEEE Transactions on Image Processing,2002,11(9):997-1013.
[11] Korneliussen J T,Hirakawa K. Camera processing with chromatic aberration[J]. IEEE Transactions on Image Processing,2014,23(10):4539-4552.
[12] Pekkucuksen I,Altunbasak Y. Multiscale gradients-based color filter array interpolation[J]. IEEE Transactions on Image Processing,2013,22(1):157-165.
[13] Sreegadha G S. Image interpolation based on multi scale gradients[J]. Procedia Computer Science,2016,85:713-724.
[14] Dubois E. Frequency-domain methods for demosaicking of Bayersampled color image[J]. IEEE Signal Processing Letters,2005,12(12):847-850.
[15] Jeon G,Dubois E. Demosaicking of noisy Bayer-sampled color images with least-squares luma-chroma demultiplexing and noise level estimation[J]. IEEE Transactions on Image Processing,2013,22(1):146-156.
[16] Su C Y. Low-complexity hybrid demosaicing for color filter arrays[J]. Journal of the Chinese Institute of Engineerings,2008,31(1):173-179.
[17]王红卫.贝尔图像插值与无损编码研究[D].太原:太原理工大学,2010.Wang H W. Reseach on Image Interpolation and Lossless Compression Based on Bayer Pattern[D]. Taiyuan:Taiyuan University of Technology,2010.
[18] Dubois E. Filter design for adaptive frequency-domain Bayer demosaicking[C]//IEEE International Conference on Image Processing. Atlanta:IEEE,2006:2705-2708.
[19] Choi M G,Jung J H,Jeon J W. No-reference image quality assessment using blur and noise[J]. International Journal of Computer Science and Engineering,2009,3(2):76-80.
[20] Aguilar M A,Saldaa M,Aguilar F J,et al. Comparing geometric and radiometric information from Geo Eye-1 and WorldView-2multispectral imagery[J]. European Journal of Remote Sensing,2014,47(1):717-738.
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