一种新颖的基于截集分解的形态学算子

数学形态学算子在机器视觉应用领域中 ,如目标识别、图像分割及缺陷探测中越来越引起人们的重视。二值形态学基本操作膨胀与腐蚀也已经扩展到灰值图像处理中。目前已存在有几种不同的灰值形态学算子的定义 ,但对于结构元为灰值图的灰值图像处理 ,还未有一种具有实时处理结构的形态学算子。文中给出了这样的一种灰值形态学算子的定义。为了进一步增强这种算子的处理能力 ,在模糊集构成的完备格框架下完成了这种算子的构造过程。     

一种新的各向异性扩散红外噪声实时抑制算法

提出一种基于各向异性扩散偏微分方程的红外图像噪声抑制算法.通过将形态学处理和红外图像局部特征相结合,建立了一种新的扩散系数.该系数利用形态学膨胀腐蚀操作获取梯度算子,改善了Perona-Malik(P-M)梯度算子对噪声的敏感性,实现了均匀区域扩散增强且边缘细节区域扩散减弱的目的.算法已在EVM-DM642硬件平台上实时运行,实验表明:它在有效平滑噪声的同时较好的保持了图像边缘细节信息.     

一种新的基于模糊推理的灰值形态学和它的光学实现

我们在文中把模糊集合理论引入到数学形态学里,提出了模糊推理形态学,导出它的基本算子和一些代数性质.对于相同的灰值图象和结构元,用该算子处理的图象较常规形态学的结果更光滑并合更多的细节.给出采用面积编码和取阈技术为基础的光学实现.最后,分析比较了模糊推理形态学与常规形态学的两种结果数据.     

一种基于修正扩展形态学算子的高光谱遥感图像端元提取算法

形态学算子反映了像素的空间相关性信息,将其应用于高光谱遥感图像端元提取可以有效地提升算法性能,本文针对已经普遍用于高光谱遥感图像端元提取的扩展形态学算子在像元排序规则和替换准则上存在的局限性,引入了基准向量的概念并给出计算方法,提出了修正扩展形态学算子.修正后的排序规则和替换准则避免了图像中不同类别交界处的交叉替换现象,保证了正确的覆盖方向,是提高端元提取效果的关键步骤.通过修正扩展形态学算子的基本膨胀和腐蚀运算,定义了相应的开-闭运算和闭-开运算,由此得出了端元判定向量,并给出端元提取算法的详细流程.基于扩展形态学的自动端元提取算法可以综合考虑光谱和空间信息,端元提取效果优于仅依靠光谱信息的算法.算法由IDL7.0实现,并在AVIRIS于Cupritc地区的高光谱遥感图像上进行实验,实验结果从光谱曲线相似性、端元平均相似度和相应地物分布图等方面证明了算法的有效性.     

一种基于修正扩展形态学算子的高光谱遥感 图像端元提取算法

形态学算子反映了像素的空间相关性信息,将其应用于高光谱遥感图像端元提取可以有效地提升算法性能.本文针对已经普遍用于高光谱遥感图像端元提取的扩展形态学算子在像元排序规则和替换准则上存在的局限性,引入了基准向量的概念并给出计算方法,提出了修正扩展形态学算子.修正后的排序规则和替换准则避免了图像中不同类别交界处的交叉替换现象,保证了正确的覆盖方向,是提高端元提取效果的关键步骤.通过修正扩展形态学算子的基本膨胀和腐蚀运算,定义了相应的开-闭运算和闭-开运算,由此得出了端元判定向量,并给出端元提取算法的详细流程.基于扩展形态学的自动端元提取算法可以综合考虑光谱和空间信息,端元提取效果优于仅依靠光谱信息的算法.算法由IDL7.0实现,并在AVIRIS于Cuprite地区的高光谱遥感图像上进行实验,实验结果从光谱曲线相似性、端元平均相似度和相应地物分布图等方面证明了算法的有效性.     

基于加权LoG算子的红外弱小目标检测方法研究

提出一种基于加权LoG算子及形态学运算的方法来提高远距离红外弱目标检测效率。通过不同尺度的加权LoG算子对图像进行运算,提取响应值最大的特征图。对图像进行形态学运算去噪,并进行Otsu二值分割聚类。输出目标点在图像上的位置坐标。实验结果表明:该方法与传统滤波方法相比,信噪比增益为36.9,杂波抑制因子为4.7,均比传统滤波方法要好。     

一种抗干扰的弱小目标检测方法

针对低信噪比灰度图像中弱小目标的检测问题,提出了SUSAN特征检测原则与数学形态学方法结合的小目标检测方法.该方法首先采用SUSAN原则利用图像灰度级直接提取特征,利用形态学算子去除噪声、分离目标.给出了应用实例,实验结果表明,这种方法抗干扰能力强,能够快速、可靠地检测出小目标.     

逻辑列阵实现的数学形态学双值像处理器

从逻辑操作的角度出发，研究了用逻辑列阵来实现数学形态学像操作的可能性，并给出了几种基本的数学形态学像操作的布尔逻辑的简化表达式，在模拟的实验装置上，完成了形态学像操作的实验，由于无需光学循环，因此，它的结构简单而且易于实现。     

基于Top-hat变换的OSAHS图像边缘检测算法

提出了一种基于多方向、多尺度Top-hat变换的图像边缘检测方法,应用于阻塞性睡眠呼吸暂停低通气综合症(Obstructive Sleep Apnea Hypopnea Syndrome, OSAHS)早期病理图像的边缘检测及诊断。首先,构造不同方向、不同尺度的Top-hat算子增强图像的对比度,利用形态学梯度进行边缘检测,然后把各个算子检测到的图像边缘按照一定的权重进行组合,得到理想的边缘,以便准确地获得病理图像的相关参数,进而实现医学电子诊断。本文以口腔图像、咽喉声带处图像、鼻道内部图像的处理为例,这三组图像的处理结果表明,与传统的边缘算子相比较,该方法能使图像的边缘信息更完整、更准确,图像的边缘闭合度可达到97.67%。     

基于数学形态学的Contourlet变换域图像降噪方法

提出了一种基于数学形态学的Contourlet变换域图像降噪方法.首先对输入的带噪图像进行多尺度、多方向的Contourlet稀疏变换,然后利用数学形态学算子在Contourlet域对高频系数进行处理,去除图像中具有较小支撑域的噪音,有效保留具有连续支撑域的图像边缘信息.最后通过Contourlet反变换得到预降噪图像.仿真结果表明,该方法较一般的Contourlet域收缩阈值降噪方法的降噪效果好,提高了PSNR值并降低了MSE值,获得更好的图像恢复质量.     

Optical greyscale morphological transformations

Greyscale morphology is more efficient and useful for processing greyscale image. It is the extension of binary morphology by use of a min or max operations. Optics is suitable for the implementation of morphological transformations because of its parallelism. However, greyscale morphology with both greyscale images and greyscale structuring elements is difficult to realize threshold decomposition since it does not commute with threshold. We propose a correlation approach for greyscale morphological transformations using area-coding technique to represent the umbra of surfaces of both greyscale image and greyscale structuring element. A primary experiment of greyscale dilation is presented.     

基于形态学水线区域的深度图像分割

深度图像分割是基于特征关系图匹配的曲面物体识别中的关键技术之一,针对已有深度图像分割方法存在的问题,提出了一种基于二值形态学的水线区域增长算法对深度图像进行分割。首先用结构元素迭代腐蚀深度图像形成距离图像;然后根据距离图像计算极限腐蚀的集合,提取出目标的种子点;最后用条件粗化从种子点开始生长回到原尺寸但不使各区域相连,完成深度图像的分割。实验证明,算法的分割结果与人的主观视觉感知具有良好的一致性。     

Extended logical function morphological operations and its optical implementation

Logical function morphology is discussed by obtaining low threshold (1 or 0 threshold). Eighteen new extended logical function morphological operations are obtained. Among them, there are eight pairs of duality operations. The principle is demonstrated by the incoherent three-plane two-lens optical correlator, in which accumulated errors can be successfully avoided by obtaining low threshold.     

Linear Separability of Positive Self-Dual Logical Filters

The threshold logic filter is an important nonlinear filter class, which is defined by a threshold logic function of binary input values. It is proved in this paper that not all positive self-dual logical functions are threshold functions if the number of input variables is 5 or more. The positive self-dual logical filter is a limited class but includes almost all filters for noise removal. Our result means that not all positive self-dual filters can be expressed by one operation of the threshold logic filters. In the sense of the filter expression by neural networks, the two-layer network cannot always optimize even this limited class.     

Multiscale top-hat selection transform based infrared and visual image fusion with emphasis on extracting regions of interest

To effectively combine regions of interest in original infrared and visual images, an adaptively weighted infrared and visual image fusion algorithm is developed based on the multiscale top-hat selection transform. First, the multiscale top-hat selection transform using multiscale structuring elements with increasing sizes is discussed. Second, the image regions of the original infrared and visual images at each scale are extracted by using the multiscale top-hat selection transform. Third, the final fusion regions are constructed from the extracted multiscale image regions. Finally, the final fusion regions are combined into a base image calculated from the original images to form the final fusion result. The combination of the final fusion regions uses the adaptive weight strategy, and the weights are adaptively obtained based on the importance of the extracted features. In the paper, we compare seven image fusion methods: wavelet pyramid algorithm (WP), shift invariant discrete wavelet transform algorithm (SIDWT), Laplacian pyramid algorithm (LP), morphological pyramid algorithm (MP), multiscale morphology based algorithm (MSM), center-surround top-hat transform based algorithm (CSTHT), and the proposed multiscale top-hat selection transform based algorithm. These seven methods are compared over five different publicly available image sets using three metrics of spatial frequency, mean gradient, and Q. The results show that the proposed algorithm is effective and may be useful for the applications related to the infrared and visual image fusion.     

One-operation image algebra for optical processing

A binary image algebra with one operation of a logic operation followed by a dilation and its modification with three additional operations for threshold processing of grey level images are developed in this paper. All the binary image processing functions and various grey level image processing functions related to morphological operations can be represented by the algebraic structure. The algebra is particularly suitable for parallel processing by optics in a cellular logic image processor architecture.     

Image enhancement through contrast enlargement using the image regions extracted by multiscale top-hat by reconstruction

An image enhancement algorithm based on multiscale top-hat by reconstruction is proposed in this paper. Firstly, multiscale top-hat by reconstruction using multiscale structuring elements is discussed. Then, multiscale bright and black image regions are extracted. Thirdly, useful image regions for image enhancement are obtained from the extracted multiscale bright and black image regions. Finally, after a base image is calculated from the results of the opening and closing by reconstruction operations, the original image is enhanced through combing the useful image regions into the base image. Experimental results on different types of images show that the proposed algorithm is efficient.     

Time-varying coupling-induced logical stochastic resonance in a periodically driven coupled bistable system

Coupling-induced logical stochastic resonance(LSR) can be observed in a noise-driven coupled bistable system where the behaviors of system can be interpreted consistently as a specific logic gate in an appropriate noise level. Here constant coupling is extended to time-varying coupling, and then we investigate the effect of time-varying coupling on LSR in a periodically driven coupled bistable system. When coupling intensity oscillates periodically with the same frequency with periodic force or relatively high frequency, the system successfully yields the desired logic output. When coupling intensity oscillates irregularly with phase disturbance, large phase disturbance reduces the area of optimal parameter region of coupling intensity and response speed of logic devices. Although the system behaves as a desired logic gate when the frequency of time-periodic coupling intensity is precisely equal to that of periodic force, the desired logic gate is not robust against tiny frequency difference and phase disturbance. Therefore, periodic coupling intensity with high frequency ratio is an optimal option to obtain a reliable and robust logic operation.     

单通道光学相关实现击中与否运算

给出了一种单通道光学相关实现击中与否运算的算法和光学装置，此法基于形态学中的腐蚀运算和光学相关的关系及阈值操作，在非相干光学相关器中，将前景结构核元素编码为１，背景结构核元素编码为ａ（ａ满足一定条件），只需用原图像与前景和背景结构进行相关，然后对相关结果取阈值的Ｋ（前景结构核元素的像素数）即可得到击中与否运算，击中与否运算可以光学并行一步实现。