计算机科学 ›› 2021, Vol. 48 ›› Issue (6): 138-144.doi: 10.11896/jsjkx.200600017
宋昱, 孙文赟
SONG Yu, SUN Wen-yun
摘要: 现有的边缘检测方法在含噪图像中的检测性能不佳。针对含噪图像的边缘检测问题,提出了利用引导核改进基于非线性结构张量的含噪图像边缘检测方法。首先,计算含噪图像的张量积。然后,根据图像梯度对张量积进行扩散,图像梯度依赖张量积本身。扩散方程中的扩散矩阵包含张量积,该张量积是通过各向异性的引导核进行空间自适应平均,而不是通过各向同性的高斯核进行平均。最后计算扩散张量积的特征值和特征向量,并基于此检测图像的边缘。将所提方法与基于线性结构张量的边缘检测方法、基于张量梯度扩散的非线性结构张量的边缘检测方法、基于图像梯度扩散的非线性结构张量的边缘检测方法进行比较,实验结果表明,所提方法可以得到更为清晰的边缘,并且检测结果中噪声较少。
中图分类号:
[1]SATHIYA L,PALANISAMY V.Minor finger knuckle printimage edge detection using second order derivates[C]//International Conference on Trends in Electronics and Informatics.Tirunelveli,India:IEEE,2019:1227-1231. [2]PRATHUSHA P,JYOTHI S,MAMATHA D M.Enhanced ima-ge edge detection methods for crab species identification[C]//International Conference on Soft-computing and Network Secu-rity.Coimbatore,India:IEEE,2018: [3]KHAIRUDIN M,IRMAWATI D.Comparison methods of edge detection for USG images[C]//International Conference on Information Technology,Computer,and Electrical Engineering.Semarang,Indonesia:IEEE,2016:85-88. [4]HE J,ZHANG S,YANG M,et al.Bi-directional cascade net-work for perceptual edge detection[C]//Conference on Compu-ter Vision and Pattern Recognition.Long Beach,USA:IEEE,2019:3823-3832. [5]DONG X,LI M,MIAO J,et al.Edge detection operator for underwater target image[C]//International Conference on Image,Vision and Computing.Chongqing,China:IEEE,2018:91-95. [6]VIKAS P,LAKSHMI M,RAJKUMAR M,et al.Edge detection in noisy images using wavelet transform[C]//Conference on Recent Advances in Electronics and Computer Engineering.Roorkee,India:IEEE,2015:36-39. [7]CHO W,JEON J.Edge detection in wavelet transform domain[C]//Korea-Japan Joint Workshop on Frontiers of Computer Vision.Mokpo,South Korea:IEEE,2015. [8]HAHN J,LEE C O.A nonlinear structure tensor with the diffusivity matrix composed of the image gradient[J].J.Math.Imaging.Vis.,2009,34:137-151. [9]PERONA P,MALIK J.Scale-space and edge detection using ani-sotropic diffusion[J].IEEE T.Pattern.Anal.,1990,12(7):629-639. [10]WEICKERT J,ROMENY B M H,VIERGEVER M A.Efficient and reliable schemes for nonlinear diffusion filtering[J].IEEE Transactions on Image Processing,1998,7(3):398-410. [11]FELSBERG M.Autocorrelation-driven diffusion filtering[J].IEEE Transactions on Image Processing,2011,20(7):1797-1806. [12]HAM B,MIN D,SOHN K.Robust scale-space filter using se-cond-order partial differential equations[J].IEEE Transactions on Image Processing,2012,21(9):3937-3951. [13]PLONKA G,MA J.Nonlinear regularized reaction-diffusion filters for denoising of images with textures[J].IEEE Transactions on Image Processing,2008,17(8):1283-1294. [14]WEICKERT J.Coherence-enhancing diffusion filtering[J].Int.J.Comput.Vision.,1999,31(2/3):111-127. [15]TSCHUMPERLE D,DERICHE R.Diffusion PDEs on vector-values images[J].IEEE Signal.Proc.Mag.,2002,19(5):16-25. [16]SERTCELIK I,KAFADAR O.Application of edge detection to potential field data using eigenvalue analysis of structure tensor[J].J.Appl.Geophys.,2012,84:86-94. [17]MA G,YU P.Comment on:SERTCELIK I,KAFADAR O,‘Application of edge detection to potential field data using eigenvalue analysis of structure tensor’[J].J.Appl.Geophys.,2013,101:142-143. [18]DORE V,MOGHADDAM R F,CHERIET M.Non-local adaptive structure tensors application to anisotropic diffusion and shock filtering[J].Image and Vision Computing,2011,29:730-743. [19]BROX T,WEICKERT J,BURGETH B,et al.Nonlinear structure tensors[J].Image and Vision Computing,2006,24:41-55. [20]LI F,PI L,ZENG T.Explicit coherence enhancing filter with spatial adaptive elliptical kernel[J].IEEE Signal.Proc.Let.,2012,19(9):555-558. [21]TAKEDA H,FARSIU S,MILANFAR P.Kernel regression for image processing and reconstruction[J].IEEE Transactions on Image Processing,2007,2(16):349-366. [22]CHATTERJEE P,MILANFAR P.Clustering-based denoisingwith locally learned dictionaries[J].IEEE Transactions on Ima-ge Processing,2009,18(7):1438-1451. |
[1] | 程成, 降爱莲. 基于多路径特征提取的实时语义分割方法 Real-time Semantic Segmentation Method Based on Multi-path Feature Extraction 计算机科学, 2022, 49(7): 120-126. https://doi.org/10.11896/jsjkx.210500157 |
[2] | 李野, 陈松灿. 基于物理信息的神经网络:最新进展与展望 Physics-informed Neural Networks:Recent Advances and Prospects 计算机科学, 2022, 49(4): 254-262. https://doi.org/10.11896/jsjkx.210500158 |
[3] | 朱戎, 叶宽, 杨博, 谢欢, 赵蕾. 基于改进DeeplabV3+的地物分类方法研究 Feature Classification Method Based on Improved DeeplabV3+ 计算机科学, 2021, 48(11A): 382-385. https://doi.org/10.11896/jsjkx.201100184 |
[4] | 刘俊琦, 李智, 张学阳. 基于视觉显著性的海面船只候选区域检测方法 Candidate Region Detection Method for Maritime Ship Based on Visual Saliency 计算机科学, 2020, 47(6A): 237-241. https://doi.org/10.11896/JsJkx.191000196 |
[5] | 周岳勇,程江华,刘通,王洋,陈明辉. 高分辨率SAR图像道路提取综述 Review of Road Extraction for High-resolution SAR Images 计算机科学, 2020, 47(1): 124-135. https://doi.org/10.11896/jsjkx.190100033 |
[6] | 霍星, 费志伟, 赵峰, 邵堃. 深度学习在驾驶员安全带检测中的应用 Application of Deep Learning in Driver’s Safety Belt Detection 计算机科学, 2019, 46(6A): 182-187. |
[7] | 王亚鸽, 康晓东, 郭军, 洪睿, 李博, 张秀芳. 一种联合Canny边缘检测和SPIHT的图像压缩方法 Image Compression Method Combining Canny Edge Detection and SPIHT 计算机科学, 2019, 46(6A): 222-225. |
[8] | 李昌兴, 武洁. 基于FPDEs与CBF的红外与可见光图像融合 Infrared Image and Visible Image Fusion Based on FPDEs and CBF 计算机科学, 2019, 46(1): 297-302. https://doi.org/10.11896/j.issn.1002-137X.2019.01.046 |
[9] | 王智慧, 李佳桐, 谢斯言, 周佳, 李豪杰, 樊鑫. 两阶段的视频字幕检测和提取算法 Two-stage Method for Video Caption Detection and Extraction 计算机科学, 2018, 45(8): 50-53. https://doi.org/10.11896/j.issn.1002-137X.2018.08.009 |
[10] | 周建,徐海芹. 一种基于核密度估计的图像边缘检测方法 Image Edge Detection Method Based on Kernel Density Estimation 计算机科学, 2018, 45(6A): 239-241. |
[11] | 李姗姗,陈莉,张永新,袁娅婷. 基于RPCA的图像模糊边缘检测算法 Fuzzy Edge Detection Algorithm Based on RPCA 计算机科学, 2018, 45(5): 273-279. https://doi.org/10.11896/j.issn.1002-137X.2018.05.047 |
[12] | 钱江,王凡,郭庆杰. 二元非张量积型连分式插值 Bivariate Non-tensor-product-typed Continued Fraction Interpolation 计算机科学, 2018, 45(3): 83-91. https://doi.org/10.11896/j.issn.1002-137X.2018.03.014 |
[13] | 余小庆, 陈仁文, 唐杰, 许锦婷. 融合小波变换和新形态学的含噪图像边缘检测 Edge Detection for Noisy Image Based on Wavelet Transform and New Mathematical Morphology 计算机科学, 2018, 45(11A): 194-197. |
[14] | 邵鹏, 周伟, 李光泉, 吴志健. 一种后处理式的改进抗锯齿算法 Improved Anti-aliasing Algorithm Based on Deferred Shading 计算机科学, 2018, 45(11A): 218-221. |
[15] | 张秀峰, 王娟, 丁强. 智能钢轨磨耗检测方法的研究 Research on Intelligent Detection Method of Steel Rail Abrasion 计算机科学, 2018, 45(11A): 274-277. |
|