基于方向导数的地震剖面图像分割仿真
|
摘要
利用人工地震波进行的地震勘探是目前寻找石油及天然气的主要方法。利用数字图像处理和模式识别技术来自动分割和识别地震剖面图,在油气勘探中具有重要的应用前景。由于地震数据非常庞大,为了在保证分割有效性的前提下提高实时识别能力,提出了基于方向导数的纹理分割法。将方向导数用于提取纹理的微观特征并结合laws纹理能量测度组成特征向量,通过FCM的分类来进行分割。该方法简单,容易实现,并且在分割边缘上具有较低的错分率。最后在Matlab平台上对真实的地震剖面图像进行了纹理分割仿真,得到较好的分割结果。
A texture segmentation method based on orientation derivative is proposed.This method uses orientation derivative to get the micro-texture characteristics and the laws of texture energy measure for getting six-dimensional eigenvector and it is classified by FCM to finish segmentation.The method is simple and easy to realize,it has less mistakes on the brim.The method is applied to the segmentation of seismic section images and has obtained better segmentation result.
A texture segmentation method based on orientation derivative is proposed.This method uses orientation derivative to get the micro-texture characteristics and the laws of texture energy measure for getting six-dimensional eigenvector and it is classified by FCM to finish segmentation.The method is simple and easy to realize,it has less mistakes on the brim.The method is applied to the segmentation of seismic section images and has obtained better segmentation result.
引文
[1]V S John.Structural Analysis of Flow-related Textures in Lavas[J].Earth-science Review,2002,57(3):279-297.
[2]MNagao,HTanabe and K Ito.Agricultural land use classificationof aerial photographs by histogram similarity method[J].On Pat-tern Recognition,Coronado,Calif.,1976.669-672.
[3]J O Eklndh.On the use of Fourier phase features for texture dis-crimination[J].Comput Graphics Image Process,1979,9(2):199-201.
[4]MMGalloway.Texture analysis using gray level run lengths[J].Computer Graphics Image Process,1975,11(4):172-179.
[5]R M Haralick,K Shanumugam and I Dinstein.Textural featuresfor image classification[J].IEEE Trans.Sytems,Man,Cyber-net.,1973,3(6):145-153.
[6]K I Law.Texture energy measures[M].Image UnderstandingWorkshop.1979.47-51.
[7]O D Faugeras and WKPratt.Décor relation methods of texture se-lection[J].IEEE Trans.Pattern Anal.Machine Intell.,1980,8(2):323-332.
[8]P Desouza.Texture recognition via auto regression[J].PatternRecognition,1982,15(6):471-475.
[9]B S Manjunath and R Chellappa.Unsupervised texture segmenta-tion using Markov random field models[J].IEEE Trans.PatternAnal.Machine Intell.,1991,3(5):478-482.
[10]H Derin and H Elliott.Modeling and segmentation of noisy andtextured images using Gibbs random fields[J].IEEE Trans.Pat-tern Anal.Machine Intell,1987,9(1):39-55.
[11]J MKeller,S Chen and R MCrownover.Texture description andsegmentation through fractal geometry[J].Comput.VisionGraphics Image Process,1989,45(2):150-166.
[12]A P Pentland.Fractal texture[M].In Proc.ISCAI 83,Karlsru-he,Germany,1983.71-83.
[13]L Dinstein,et al.Astructural analyzer for regularly arranged tex-tured region[C].Proceedings of 7ICPR,1984,8(3):361-364.
[14]G H Granlund.Desription of texture using the general operatorapproaches[C].Proceedings of 5ICPR,1980.361-364.
[15]A K Jain,F Farrokhnia.Unsupervised Texture Segmentation U-sing Gabor Filter[J].Pattern Recognition,1991,24(12):1167-1186.
[16]Zhen Zhang.AKnowledge-based System Controlled by an Itera-tive Quadtree Splitting Scheme for Segmentation of Seismic Sec-tions[J].IEEE Trans.On Geoscience and Remote Sensing,1998,26(5):518-524.
[17]黄伟.地震剖面图像纹理分割研究综述[J].韩山师范学院学报,2007,(3):103-107.
[2]MNagao,HTanabe and K Ito.Agricultural land use classificationof aerial photographs by histogram similarity method[J].On Pat-tern Recognition,Coronado,Calif.,1976.669-672.
[3]J O Eklndh.On the use of Fourier phase features for texture dis-crimination[J].Comput Graphics Image Process,1979,9(2):199-201.
[4]MMGalloway.Texture analysis using gray level run lengths[J].Computer Graphics Image Process,1975,11(4):172-179.
[5]R M Haralick,K Shanumugam and I Dinstein.Textural featuresfor image classification[J].IEEE Trans.Sytems,Man,Cyber-net.,1973,3(6):145-153.
[6]K I Law.Texture energy measures[M].Image UnderstandingWorkshop.1979.47-51.
[7]O D Faugeras and WKPratt.Décor relation methods of texture se-lection[J].IEEE Trans.Pattern Anal.Machine Intell.,1980,8(2):323-332.
[8]P Desouza.Texture recognition via auto regression[J].PatternRecognition,1982,15(6):471-475.
[9]B S Manjunath and R Chellappa.Unsupervised texture segmenta-tion using Markov random field models[J].IEEE Trans.PatternAnal.Machine Intell.,1991,3(5):478-482.
[10]H Derin and H Elliott.Modeling and segmentation of noisy andtextured images using Gibbs random fields[J].IEEE Trans.Pat-tern Anal.Machine Intell,1987,9(1):39-55.
[11]J MKeller,S Chen and R MCrownover.Texture description andsegmentation through fractal geometry[J].Comput.VisionGraphics Image Process,1989,45(2):150-166.
[12]A P Pentland.Fractal texture[M].In Proc.ISCAI 83,Karlsru-he,Germany,1983.71-83.
[13]L Dinstein,et al.Astructural analyzer for regularly arranged tex-tured region[C].Proceedings of 7ICPR,1984,8(3):361-364.
[14]G H Granlund.Desription of texture using the general operatorapproaches[C].Proceedings of 5ICPR,1980.361-364.
[15]A K Jain,F Farrokhnia.Unsupervised Texture Segmentation U-sing Gabor Filter[J].Pattern Recognition,1991,24(12):1167-1186.
[16]Zhen Zhang.AKnowledge-based System Controlled by an Itera-tive Quadtree Splitting Scheme for Segmentation of Seismic Sec-tions[J].IEEE Trans.On Geoscience and Remote Sensing,1998,26(5):518-524.
[17]黄伟.地震剖面图像纹理分割研究综述[J].韩山师范学院学报,2007,(3):103-107.
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心