基于彩色空间变换的迭代反射投影遥感影像的超分辨率重建
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摘要
针对单帧迭代反射投影影像存在重建质量不高的问题,本文在分析了彩色空间变换和迭代反射投影算法的基础上,提出了一种基于彩色空间变换和迭代反射投影相结合的超分辨率重建算法。该算法结合了彩色空间变换和迭代反射投影算法的优势,通过彩色空间变换将RGB彩色空间转换到YCbCr彩色空间,对亮度信息分量Y进行迭代反射投影算法使得重构误差最小化。在Cb和Cr两个色差分量通道采用简单的双三次插值算法来降低算法复杂度,最后将重建得到的结果转换回RGB彩色空间。实验结果表明:该算法得到结果与现有其他算法相比得到的峰值信噪比高,且运算复杂度低,可明显提高重建质量。
For the problem of single super resolution reconstruction,we analysis the color space transformation and iterative back projection algorithm,we propose a super resolution reconstruction algorithm based on a combination of color space transform and iterative back algorithm. The algorithm combines the advantage of the color space transformation and iterative back projection algorithm,the color space transformation converts the RGB color space to YCb Cr color space,we use iterative reflective projection algorithm in Y channel to make the reconstruction error minimization. And we use the bicubic interpolation algorithm in CB and Cr channel to reduce the complexity of the algorithm,finally we will transformed the reconstruct results into the RGB color space. Experimental results show that the proposed algorithm has higher peak signal-to-noise ratio and lower computational complexity compared with other existing algorithms,and improves the quality of reconstruction significantly.
For the problem of single super resolution reconstruction,we analysis the color space transformation and iterative back projection algorithm,we propose a super resolution reconstruction algorithm based on a combination of color space transform and iterative back algorithm. The algorithm combines the advantage of the color space transformation and iterative back projection algorithm,the color space transformation converts the RGB color space to YCb Cr color space,we use iterative reflective projection algorithm in Y channel to make the reconstruction error minimization. And we use the bicubic interpolation algorithm in CB and Cr channel to reduce the complexity of the algorithm,finally we will transformed the reconstruct results into the RGB color space. Experimental results show that the proposed algorithm has higher peak signal-to-noise ratio and lower computational complexity compared with other existing algorithms,and improves the quality of reconstruction significantly.
引文
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[2]杨学峰.遥感图象频域和空域超分辨重建技术研究[D].哈尔滨:哈尔滨工业大学,2011.
[3]王金亮,曾浩,王艳英,等.基于小波分析的TM遥感图像超分辨率重建[J].遥感技术与应用,2016,31(3):476-480.
[4]宋佳伟,徐煜明,肖贤建.基于小波变换和迭代反向投影的超分辨率算法[J].计算机技术与发展,2015(2):74-77.
[5]贺清碧,黄大荣,杨永琴.基于小波分析和多项式细分定位的超分辨率图像重建算法[J].计算机科学,2016,43(3):313-316.
[6] Lai R,Yang Y T,Zhou H X,et al. Total variation regularized iterative back-projection method for single frame image super resolution[C]//IEEE,International Conference on Signal Processing. IEEE,2012.
[7] Rasti P,Demirel H,Anbarjafari G.Improved Iterative Back Projection for video super-resolution[C]//Signal Processing and Communications Applications Conference.IEEE,2014.
[8] Li H,Lam K M.Guided iterative back-projection scheme for single-image super-resolution[C]//Global High Tech Congress on Electronics.IEEE,2013.
[9]沈焕锋,李平湘,张良培.一种基于正则化技术的超分辨影像重建方法[J].中国图象图形学报,2005,10(4):436-440.
[10]陶洪久,饶俊飞,周祖德.单幅图像的超分辨率重建方法[J].武汉理工大学学报:交通科学与工程版,2004,28(6):943-946.
[11]肖宿,韩国强,沃焱.数字图像超分辨率重建技术综述[J].计算机科学,2009,36(12):8-13.
[12]刘薇,朱虹,刘小乾.一种退化模型估计的超分辨率重建方法[C]//全国图象图形联合学术会议.西安:陕西省图像图形学学会,2013.
[13] Mayyas K,Aboulnasr T. Leaky LMS algorithm:MSE analysis for Gaussian data[J]. IEEE Transactions on Signal Processing,1997,45(4):927-934.
[14] Lee B,Kim M.No-Reference PSNR Estimation for HEVC Encoded Video[J]. IEEE Transactions on Broadcasting,2013,59(1):20-27.