基于可重构计算技术的图像识别与分类系统研究
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摘要
随着图像自动目标识别和分类技术应用领域的迅速拓展,对计算机处理能力的要求越来越高。可重构计算是随着电子技术的进步而发展起来的一种新的计算技术,它将微处理器的灵活性和ASIC的高效性结合起来,使图像实时处理技术的快速实现成为可能。
本论文在综合分析当前图像目标识别和分类算法特点的基础上,深入研究了SAR图像本身的特性,目标的特征和提取方法,并对利用可重构计算技术实现图像识别和分类的方法做了有益的研究和探讨。本文的主要工作和创新之处包括:
(1)研究了遥感图像特点及目标识别的方法,提出了一种基于模板的图像识别算法。
遥感图像以其覆盖面积大、时效性强、数据综合性高等特点成为了国民经济各个部门重要的数据来源,因此遥感图像处理成为当今计算机应用领域的热点。SAR图像地物目标可分为点目标、线目标、面目标以及这三者在有限尺度内组合成的硬目标。大多数人造目标属于硬目标。SAR图像中显示的硬目标并非人们平常感知的视觉形象,只有在雷达分辨率较高的时候硬目标才能显示出一定的目标细节,必须充分分析目标的特征才能较好的对目标进行识别。本文在分析SAR图像自动识别过程,并结合国内外研究的经验的基础上,提出基于模板的自动目标识别算法。通过对图像进行有效的预处理,将目标集中在一个含有较少背景的区域中,不仅减少了背景对目标检测的影响,而且大大减少了目标检测时的数据量。并且通过对目标特征进行大量分析,获得了行之有效的模板,提高了识别率。
(2)研究了图像噪声、纹理特征及支持向量机分类器,提出了一种基于纹理的图像分类算法。
图像分类是根据像元的灰度信息以及其他空间特征,判定图像中地物类别的过程。在遥感图像技术中,无论是专业信息提取、运动变化预测,还是专题地图制作和建立遥感数据库等都离不开遥感图像的分类。根据求解判别函数是否利用了类别的先验知识,图像分类的方法可以归结为监督分类法和非监督分类法。非监督分类的结果只是对不同类别达到区分,并不能确定类别的属性,且准确性和收敛速度较差。本文深入研究了图像的有监督分类方法。在分析已有算法不足的基础上,选择支撑向量机作为分类器,通过对SAR图像有效去噪和纹理特征的提取,不仅减少了无关特征向量的计算,而且提高了图像分类的正确率。
(3)研究了软硬件协同设计方法学,提出了将基于模块的部分重构技术应用于图像识别算法设计与实现的方法。
根据高分辨率图像的目标识别低层算法处理数据量大、算法较简单等特点,提出了在可重构平台上以软硬件协同的模式实现目标识别的方法。首先针对可重构计算平台的特点分析了图像识别的算法,再借鉴模块化的设计方法的思路完成各个模块的设计与实现,最终利用可重构逻辑器件的部分重构特性实现系统运行时重构。设计文件不仅能够普遍适用于Virtex系列的可重构逻辑器件,而且适用于各种图源图像的预处理方法,为其他相关图像处理算法的可重构实现奠定了良好的基础。可重构平台上以软硬件协同工作的模式的引入,不仅准实时的实现了目标识别方法,而且减少了芯片的使用面积,降低了可重构器件的布线难度。
(4)研究了图像纹理计算的特点及部分重构方法学,提出了将基于差异的部分重构技术应用于实现图像分类算法设计与实现的方法。
基于灰度共生矩阵的纹理普遍应用于各种图源的分类和特征提取。针对软件实现纹理计算量大、时间长的问题,传统的方法只能将图像降维或者降阶,这显然会影响后续特征提取时的效果。本文提出的方法首先针对可重构平台的特点分析了图像分类方法,然后利用基于差异的部分重构技术完成了系统设计。使图像纹理的计算,乃至整个图像分类的速度达到了准实时性。系统的设计文件不仅具有良好的可移植性,而且只需很少的改动就可以实现其他图源的图像快速分类。实验表明,基于差异的动态可重构方法的引入,与通用处理器相比图像分类速度,节约芯片使用面积。
Along with the rapid expansion of application areas of image automatic target recognition (ATR) and classification technology, the demand of computer processing abilities is getting higher. Reconfigurable computing is a brand-new technology which is developing with the progress of electronic technology. It combines microprocessor's flexibility and ASIC’s efficiency, and makes the realization of real-time image processing technology rapidly and possibly.
Based on comprehensive analysis of current image recognition and classification algorithms’characteristics, deeply investigation of SAR image’s behaviors, target’s features and extraction methods, this thesis has done the beneficial researches and discussions to the usage of reconfigurable computing technology to realize the algorithms of image recognition and classification. The main tasks and the innovations of this thesis include:
(1) A study of traits of remote sensing image and algorithms of target recognition was made, a feature templates matching based ATR algorithm is proposed.
Because of wide coverage, in-time and comprehensive data etc., remote sensing image becomes an important data source for every branch of national economy and remote sensing imagery processing turns into hotspot in field of computer-based applications at present. The ground objects of SAR imagery can be divided into point target, line target, area target and hard target that combine by them in limited scales. Most of artificial targets are hard targets. The hard target that displayed in SAR image is not so similar to ordinary sensation visual image. The details of the targets reveal if and only if the radar resolution is high enough, so the recognition preferably when the targets’features are sufficiently analyzed. After analysis SAR ATR process and in the light of domestic and foreign research experience, a templates matching based ATR algorithm is proposed. Via effectual pretreatment of goal image, the targets limited in regions that content less background. This method can not only decrease the background’s influence to target detection but also reduce the data size. Though analyze to the features of the targets, workable templates are gained and recognition rate is enhanced.
(2) Research on pattern noise, textural property and support vector machine, a texture based image classification algorithm is proposed.
Image classification is a kind of procedure that according to the pixels’grey scale and space characterization to justify the category of ground object. In application of sensing image, image classification is demanded in specialized information extraction, motion prediction, making thematic map, establishment remote sensing database and so on. Depending on whether the priori knowledge is utilized in discriminant function’s solving, the classification methods can be referred to supervised and unsupervised. Unsupervised methods can only find differing aspects among the samples but cannot fix the property, so the accuracy and velocity of convergence are relatively poor. This thesis focuses on supervised methods. After discussion the insufficient of available method, SVM is chose as classify. Though effectively denoise and extraction the textural property, the computation of the irrelevant eigenvector is reduced and the rate of correct is improved.
(3) Investigate the methodology of hardware/software co-design and apply the module-based reconfiguration design method to implement the image recognition.
In terms of large data size and simple realization characters in low level of recognition of high-resolution image, a reconfigurable platform based hardware/software co-design method is proposed. Analysis the proposed image recognition algorithm in connection with the characteristics of reconfigurable platform in the first place. And then designs each module by using modular design methodology. Finally implements the run-time partial reconfiguration in actual devices. The design documents are not only universally valid in Virtex series reconfigurable logical component, but also can be used in pretreatment all sources of image and have laid a good foundation for realizing other interrelated image processing algorithms. Results show that the system can improve the recognition rate significantly, have better speed performance when compared to a general purpose processor, save the used chip area and lower complexity of place and route.
(4) A broad survey of image texture computation characteristic and partial reconfiguration methodological problems and apply the difference-based partial dynamic reconfiguration method to realize image classification.
The texture which based on GLCM is widely used in all kind of images’classification and feature extraction. The heavy computation load and long time problem when using software to calculate the texture can only be endured by dimensionality reduction or deflation traditionally. But that obviously lower the amount of effect of follow-up feature extraction. After analysis the proposed image classification algorithm directed towards the characteristics of reconfigurable platform, the system design is completed by using difference-based partial dynamic reconfiguration method which made the calculation of texture and even image classification become quasi real time. System's design document has good portability and possible to realize the other source image classification quickly if a very few modification be made. Results show that when a difference-based partial dynamic reconfiguration method introduced, the system can improve the classification speed and save the used chip area.
本论文在综合分析当前图像目标识别和分类算法特点的基础上,深入研究了SAR图像本身的特性,目标的特征和提取方法,并对利用可重构计算技术实现图像识别和分类的方法做了有益的研究和探讨。本文的主要工作和创新之处包括:
(1)研究了遥感图像特点及目标识别的方法,提出了一种基于模板的图像识别算法。
遥感图像以其覆盖面积大、时效性强、数据综合性高等特点成为了国民经济各个部门重要的数据来源,因此遥感图像处理成为当今计算机应用领域的热点。SAR图像地物目标可分为点目标、线目标、面目标以及这三者在有限尺度内组合成的硬目标。大多数人造目标属于硬目标。SAR图像中显示的硬目标并非人们平常感知的视觉形象,只有在雷达分辨率较高的时候硬目标才能显示出一定的目标细节,必须充分分析目标的特征才能较好的对目标进行识别。本文在分析SAR图像自动识别过程,并结合国内外研究的经验的基础上,提出基于模板的自动目标识别算法。通过对图像进行有效的预处理,将目标集中在一个含有较少背景的区域中,不仅减少了背景对目标检测的影响,而且大大减少了目标检测时的数据量。并且通过对目标特征进行大量分析,获得了行之有效的模板,提高了识别率。
(2)研究了图像噪声、纹理特征及支持向量机分类器,提出了一种基于纹理的图像分类算法。
图像分类是根据像元的灰度信息以及其他空间特征,判定图像中地物类别的过程。在遥感图像技术中,无论是专业信息提取、运动变化预测,还是专题地图制作和建立遥感数据库等都离不开遥感图像的分类。根据求解判别函数是否利用了类别的先验知识,图像分类的方法可以归结为监督分类法和非监督分类法。非监督分类的结果只是对不同类别达到区分,并不能确定类别的属性,且准确性和收敛速度较差。本文深入研究了图像的有监督分类方法。在分析已有算法不足的基础上,选择支撑向量机作为分类器,通过对SAR图像有效去噪和纹理特征的提取,不仅减少了无关特征向量的计算,而且提高了图像分类的正确率。
(3)研究了软硬件协同设计方法学,提出了将基于模块的部分重构技术应用于图像识别算法设计与实现的方法。
根据高分辨率图像的目标识别低层算法处理数据量大、算法较简单等特点,提出了在可重构平台上以软硬件协同的模式实现目标识别的方法。首先针对可重构计算平台的特点分析了图像识别的算法,再借鉴模块化的设计方法的思路完成各个模块的设计与实现,最终利用可重构逻辑器件的部分重构特性实现系统运行时重构。设计文件不仅能够普遍适用于Virtex系列的可重构逻辑器件,而且适用于各种图源图像的预处理方法,为其他相关图像处理算法的可重构实现奠定了良好的基础。可重构平台上以软硬件协同工作的模式的引入,不仅准实时的实现了目标识别方法,而且减少了芯片的使用面积,降低了可重构器件的布线难度。
(4)研究了图像纹理计算的特点及部分重构方法学,提出了将基于差异的部分重构技术应用于实现图像分类算法设计与实现的方法。
基于灰度共生矩阵的纹理普遍应用于各种图源的分类和特征提取。针对软件实现纹理计算量大、时间长的问题,传统的方法只能将图像降维或者降阶,这显然会影响后续特征提取时的效果。本文提出的方法首先针对可重构平台的特点分析了图像分类方法,然后利用基于差异的部分重构技术完成了系统设计。使图像纹理的计算,乃至整个图像分类的速度达到了准实时性。系统的设计文件不仅具有良好的可移植性,而且只需很少的改动就可以实现其他图源的图像快速分类。实验表明,基于差异的动态可重构方法的引入,与通用处理器相比图像分类速度,节约芯片使用面积。
Along with the rapid expansion of application areas of image automatic target recognition (ATR) and classification technology, the demand of computer processing abilities is getting higher. Reconfigurable computing is a brand-new technology which is developing with the progress of electronic technology. It combines microprocessor's flexibility and ASIC’s efficiency, and makes the realization of real-time image processing technology rapidly and possibly.
Based on comprehensive analysis of current image recognition and classification algorithms’characteristics, deeply investigation of SAR image’s behaviors, target’s features and extraction methods, this thesis has done the beneficial researches and discussions to the usage of reconfigurable computing technology to realize the algorithms of image recognition and classification. The main tasks and the innovations of this thesis include:
(1) A study of traits of remote sensing image and algorithms of target recognition was made, a feature templates matching based ATR algorithm is proposed.
Because of wide coverage, in-time and comprehensive data etc., remote sensing image becomes an important data source for every branch of national economy and remote sensing imagery processing turns into hotspot in field of computer-based applications at present. The ground objects of SAR imagery can be divided into point target, line target, area target and hard target that combine by them in limited scales. Most of artificial targets are hard targets. The hard target that displayed in SAR image is not so similar to ordinary sensation visual image. The details of the targets reveal if and only if the radar resolution is high enough, so the recognition preferably when the targets’features are sufficiently analyzed. After analysis SAR ATR process and in the light of domestic and foreign research experience, a templates matching based ATR algorithm is proposed. Via effectual pretreatment of goal image, the targets limited in regions that content less background. This method can not only decrease the background’s influence to target detection but also reduce the data size. Though analyze to the features of the targets, workable templates are gained and recognition rate is enhanced.
(2) Research on pattern noise, textural property and support vector machine, a texture based image classification algorithm is proposed.
Image classification is a kind of procedure that according to the pixels’grey scale and space characterization to justify the category of ground object. In application of sensing image, image classification is demanded in specialized information extraction, motion prediction, making thematic map, establishment remote sensing database and so on. Depending on whether the priori knowledge is utilized in discriminant function’s solving, the classification methods can be referred to supervised and unsupervised. Unsupervised methods can only find differing aspects among the samples but cannot fix the property, so the accuracy and velocity of convergence are relatively poor. This thesis focuses on supervised methods. After discussion the insufficient of available method, SVM is chose as classify. Though effectively denoise and extraction the textural property, the computation of the irrelevant eigenvector is reduced and the rate of correct is improved.
(3) Investigate the methodology of hardware/software co-design and apply the module-based reconfiguration design method to implement the image recognition.
In terms of large data size and simple realization characters in low level of recognition of high-resolution image, a reconfigurable platform based hardware/software co-design method is proposed. Analysis the proposed image recognition algorithm in connection with the characteristics of reconfigurable platform in the first place. And then designs each module by using modular design methodology. Finally implements the run-time partial reconfiguration in actual devices. The design documents are not only universally valid in Virtex series reconfigurable logical component, but also can be used in pretreatment all sources of image and have laid a good foundation for realizing other interrelated image processing algorithms. Results show that the system can improve the recognition rate significantly, have better speed performance when compared to a general purpose processor, save the used chip area and lower complexity of place and route.
(4) A broad survey of image texture computation characteristic and partial reconfiguration methodological problems and apply the difference-based partial dynamic reconfiguration method to realize image classification.
The texture which based on GLCM is widely used in all kind of images’classification and feature extraction. The heavy computation load and long time problem when using software to calculate the texture can only be endured by dimensionality reduction or deflation traditionally. But that obviously lower the amount of effect of follow-up feature extraction. After analysis the proposed image classification algorithm directed towards the characteristics of reconfigurable platform, the system design is completed by using difference-based partial dynamic reconfiguration method which made the calculation of texture and even image classification become quasi real time. System's design document has good portability and possible to realize the other source image classification quickly if a very few modification be made. Results show that when a difference-based partial dynamic reconfiguration method introduced, the system can improve the classification speed and save the used chip area.
引文
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