一种基于超分辨率的叠栅条纹图像处理方法
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摘要
针对叠栅条纹图像在精密测量方面的应用需求,提出了一种基于图像局部自相似性和去块效应后处理的超分辨率算法。该算法利用叠栅条纹图像的局部自相似性,首先对原始低分辨率条纹图像插值,得到初始高分辨率图像,然后寻找各高分辨率图像块对应的低分辨率最优匹配块,从高、低分辨率图像块对中提取先验知识,完成单帧图像的超分辨率重建。本文算法对图像进行了块操作,在重建结果中引入了块效应。针对该问题,同时提出了一种能够快速消除块效应的后处理算法。结果表明,将本文两种算法结合使用,能够有效提高图像质量,同时消除重建图像中块效应的影响。本文算法不需要借助外部图像,计算复杂度低,适用于叠栅条纹图像超分辨率重建。
Aiming at the applications of moiréfringes in fine measurement,a super-resolution algorithm is proposed based on local self-similarity and deblocking post-processing.In this algorithm,with the local self-similarity of moiréfringes,the initial high-resolution images are first obtained through an interpolation of the original lowresolution images.Then the optimal matching low-resolution block corresponding to each high-resolution image block is searched.The prior knowledge is extracted from the high-and low-resolution image blocks and thus the super-resolution reconstruction of a single-frame image is realized.In addition,the blocking artifacts are introduced in the reconstructed results after the blocking operations.As for this problem,apost-processing algorithm for quickly eliminating blocking artifacts is simultaneously proposed.The results show that the combination of the proposed two algorithms can effectively improve the image quality and simultaneously eliminate the blocking artifacts in the reconstruction process of images.The algorithm does not relay on external images and has a low computational complexity,suitable for the super-resolution reconstruction of moiréfringe images.
Aiming at the applications of moiréfringes in fine measurement,a super-resolution algorithm is proposed based on local self-similarity and deblocking post-processing.In this algorithm,with the local self-similarity of moiréfringes,the initial high-resolution images are first obtained through an interpolation of the original lowresolution images.Then the optimal matching low-resolution block corresponding to each high-resolution image block is searched.The prior knowledge is extracted from the high-and low-resolution image blocks and thus the super-resolution reconstruction of a single-frame image is realized.In addition,the blocking artifacts are introduced in the reconstructed results after the blocking operations.As for this problem,apost-processing algorithm for quickly eliminating blocking artifacts is simultaneously proposed.The results show that the combination of the proposed two algorithms can effectively improve the image quality and simultaneously eliminate the blocking artifacts in the reconstruction process of images.The algorithm does not relay on external images and has a low computational complexity,suitable for the super-resolution reconstruction of moiréfringe images.
引文
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[2]LüQ,Li W H,Bayanheshig,et al.Interferometric precision displacement measurement system based on diffraction grating[J].Chinese Optics,2017,10(1):39-50.吕强,李文昊,巴音贺希格,等.基于衍射光栅的干涉式精密位移测量系统[J].中国光学,2017,10(1):39-50.
[3]Chen J,Gao H B,Wang W G,et al.Methods and applications of image super-resolution restoration[J].Laser&Optoelectronics Progress,2015,52(2):020004.陈健,高慧斌,王伟国,等.图像超分辨率复原方法及应用[J].激光与光电子学进展,2015,52(2):020004.
[4]Weng J W,Tan S Y.Imaging resolution of selfinterference incoherent digital holographic system[J].Chinese Journal of Lasers,2016,43(6):0609006.翁嘉文,谭穗妍.自干涉非相干全息成像系统分辨率[J].中国激光,2016,43(6):0609006.
[5]Yao Y,Qiao Y F,Zhong X,et al.Super-resolution reconstruction of staring imaging degraded model[J].Acta Optica Sinica,2017,37(8):0810003.姚烨,乔彦峰,钟兴,等.凝视成像降质模型的超分辨率重建[J].光学学报,2017,37(8):0810003.
[6]Tsai R T,Huang T S.Multiframe image restoration and registration[J].Advances in Computer Vision and Image Processing,1984,1(7):317-339.
[7]Tan Z,Xiangli B B,LüQ B,et al.A sequence images super-resolution enhancement approach based on frequency-domain[J].Acta Optica Sinica,2017,37(7):0710001.谭政,相里斌,吕群波,等.一种基于频域的序列图像超分辨率增强方法[J].光学学报,2017,37(7):0710001.
[8]Freeman W T,Jones T R,Pasztor E C.Examplebased super-resolution[J].IEEE Computer Graphics and Applications,2002,22(2):56-65.
[9]Sun J,Xu Z B,Shum H Y.Gradient profile prior and its applications in image super-resolution and enhancement[J].IEEE Transactions on Image Processing,2011,20(6):1529-1542.
[10]Chang H,Yeung D Y,Xiong Y M.Super-resolution through neighbor embedding[C]∥IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2004,1:275-282.
[11]Gao X B,Zhang K B,Tao D C,et al.Joint learning for single-image super-resolution via a coupled constraint[J].IEEE Transactions on Image Processing,2012,21(2):469-480.
[12]Yang J,Wright J C,Huang T S,et al.Image superresolution via sparse representation[J].IEEETransactions on Image Processing,2010,19(11):2861-2873.
[13]Zeyde R,Elad M,Protter M.On single image scaleup using sparse-representations[C]∥International Conferences on Curves and Surfaces,2010:711-730.
[14]Wang J J,Zhu S H,Gong Y H.Resolution enhancement based on learning the sparse association of image patches[J].Pattern Recognition Letters,2010,31(1):1-10.
[15]Suetake N,Sakano M,Uchino E.Image superresolution based on local self-similarity[J].Optical Review,2008,15(1):26-30.
[16]Glasner D,Bagon S,Irani M.Super-resolution from a single image[C]∥IEEE International Conference on Computer Vision,2009:349-356.
[17]Lu X Q,Yuan H L,Yan P K,et al.Geometry constrained sparse coding for single image superresolution[C]∥IEEE Conference on Computer Vision and Pattern Recognition,2012:1648-1655.
[18]Freedman G,Fattal R.Image and video upscaling from local-examples[J].ACM Transactions on Graphics,2011,30(2):12-22.
[19]Coudoux F X,Gazalet M,Corlay P.Reduction of blocking effect in DCT-coded images based on a visual perception:criterion[J].Signal Processing Image Communication,1998,11(3):179-186.
[20]Karunasekera S A,Kingsbury N G.A distortion measure for blocking artifacts in images based on human visual sensitivity[J].IEEE Transactions on Image Processing,1995,4(6):713-724.
[21]Mittal A,Moorthy A K,Bovik A C.No-reference image quality assessment in the spatial domain[J].IEEE Transactions on Image Processing,2012,21(12):4695-4708.
[22]Mittal A,Soundararajan R,Bovik A C.Making a"completely blind"image quality analyzer[J].IEEESignal Processing Letters,2013,20(3):209-212.
[23]Moorthy A K,Bovik A C.Blind image quality assessment:from natural scene statistics to perceptual quality[J].IEEE Transactions on Image Processing,2011,20(12):3350-3364.