基于最大模糊熵原理的多阈值图像分割新算法

基于最大模糊熵准则,提出了一种新的多阈值图像分割算法。该算法通过定义一种简单的线性模糊隶属度函数,将图像模糊划分为若干个不同的区域;同时采用自适应遗传算法搜索最大模糊熵准则下图像的一组最佳分割阈值,并对遗传算法中的编码方式及交叉算子、变异算子进行了一些有益的改进,极大地减少了计算量和存储空间,加快了算法的搜索速度。通过仿真实验证明该算法对复杂图像良好的分割效果和较强的实时处理能力。     

Color-texture based unsupervised segmentation using JSEG with fuzzy connectedness

1.INTRODUCTIONJSEG[1]is a distinguished one in many existing seg-mentation methods based on color-texture[1,4,6~8].Itis computationally more feasible than many othermethods[1]because JSEGis to test the homogeneityof a given color-texture pattern,instead of doing pa-rameter esti mationfor a specific model like many oth-er texture segmentation algorithms.The segmentation results produced by JSEGaremainly based on a class-mapformed by the color classlabel of every pixel,which is the prod…     

基于直方图指数平滑的模糊散度图像分割

当图像灰度直方图具有多峰时,模糊散度图像分割方法的参数初始化有困难。针对这一问题,基于直方图指数平滑峰点自动检测原理,提出了一种自适应的模糊散度图像分割算法。该算法首先利用直方图指数平滑峰点自动检测原理,检测出直方图合理的波峰点和波谷点,并统计波峰的个数。然后利用检测到的波谷值初始化目标平均灰度等级搜索区间,利用波峰值初始化散度函数搜索区间,分类数由检测到的峰点个数来确定。实验结果表明,该方法更具有普遍性和适应性。     

Image segmentation algorithm based on high-dimension fuzzy character and restrained clustering network

An image segmentation algorithm of the restrained fuzzy Kohonen clustering network （RFKCN） based on high- dimension fuzzy character is proposed. The algorithm includes two steps. The first step is the fuzzification of pixels in which two redundant images are built by fuzzy mean value and fuzzy median value. The second step is to construct a three-dimensional （3-D） feature vector of redundant images and their original images and cluster the feature vector through RFKCN, to realize image seg- mentation. The proposed algorithm fully takes into account not only gray distribution information of pixels, but also relevant information and fuzzy information among neighboring pixels in constructing 3- D character space. Based on the combination of competitiveness, redundancy and complementary of the information, the proposed algorithm improves the accuracy of clustering. Theoretical anal- yses and experimental results demonstrate that the proposed algorithm has a good segmentation performance.     

基于模糊积分的图像分割算法融合

提出了一种基于多分类器融合的阈值分割方法,采用模糊积分将多种阈值分割算法的结果进行融合,其区别于现有分类器融合算法之处在于,融合过程不仅取决于各个分类器(分割算法)的判决输出,而且与各个分类器的判决能力有关。各个分类器的判决能力用模糊测度表示,它可以解释为单个分类器判决对最终融合判决的重要程度。通过使用一组手工分割的测试图像进行算法评估,结果表明,所提出的融合算法性能不仅优于单个阈值分割算法,而且优于基于多数表决和算术平均的分类器融合算法。     

2-D mini mumfuzzy entropy method of image thresholding based on genetic algorithm

1 .INTRODUCTIONI mage thresholding[1]which extracts the object fromthe backgroundin an input i mage is one of the mostcommon applicationsini mage analysis .For example ,in automatic recognition of machine printed or hand-written texts ,in shape recognition of objects ,and ini mage enhancement ,thresholding is a necessary stepfori mage preprocessing.If the object is clearly distin-guishable from the background, the gray-level his-togram will be bi modal andthe thresholdfor segmen-tation can…     

基于文化算法的C-V水平集图像分割

针对基于梯度变化的水平集图像分割对噪声敏感、不能很好地保持图像中的边缘信息、分割结果依赖初始参数、取得最优解时不能及时结束等问题,提出了一种基于文化算法的水平集图像分割算法,将文化算法应用到C-V(Chan-Vese)水平集模型之中,实现了水平集模型图像分割参数的自动选取,通过信度空间的形势知识和规范知识不断优化指导种群进化,并通过判定图像熵适应度值的变化适时终止分割过程。实验结果表明,本文方法能够准确分割出医学图像的病变区域,在抗噪声性能和分割效率方面明显优于常规方法。     

基于改进麻雀搜索算法的多阈值图像分割

针对传统多阈值图像分割方法中存在的分割精度低、计算量大、分割速度慢等问题,提出了一种基于改进麻雀搜索算法(improved sparrow search algorithm,ISSA)的多阈值图像分割方法.首先,结合鸟群算法(bird swarm algorithm,BSA)中飞行行为的思想优化麻雀搜索算法(sparr...     

广义模糊熵的构造及其在图像分割中的应用

针对现有的模糊熵阈值法对噪声干扰、光照不均匀图片的分割不能获得满意分割效果的不足,提出了模糊熵公式的参数化修改并用于图像分割,获得了选取最佳分割阈值的模糊熵新算法。首先将Sugeno广义否定算子替代二次型模糊熵公式的Zadeh标准否定算子,得到了参数型的广义模糊熵表达式;其次,将其应用于构造图像阈值化分割的准则函数;最后,给出了图像阈值化分割新算法中的广义模糊熵参数自动选取方法。实验结果表明,给出的广义模糊熵图像分割方法对光照不均匀图像相比传统模糊熵分割方法更有效。     

基于轮廓波变换和改进模糊c均值聚类的红外图像分割

针对红外图像分辨率低、对比度弱、易受噪声污染等特点,给出了轮廓波变换与模糊c均值聚类相结合的红外图像分割方法。该方法首先在假定图像轮廓波变换系数的先验为高斯分布的基础上,将基于最大后验概率准则的比例萎缩法应用于红外图像降噪,以完成分割前的预处理过程,然后利用改进的模糊c均值算法对降噪后的红外图像进行分割。针对标准模糊c均值分割存在的问题,本文提出的方法从基于样本直方图的最小最大距离法的初始聚类中心确定、考虑邻域像素相关性的样本点聚类权值和邻域隶属度修正三个方面加以改进,在保证分割精度的基础上,进一步滤除降噪阶段遗留下的图像噪声。对一系列红外图像进行实验的结果表明,相对于标准模糊c均值算法,本文提出的改进算法划分熵平均降低约10%,区域对比度提高约27%,能够实现对受到噪声污染红外图像的有效分割。     

Fast segmentation approach for SAR image based on simple Markov random field

Traditional image segmentation methods based on MRF converge slowly and require pre-defined weight. These disadvan-tages are addressed, and a fast segmentation approach based on simple Markov random field (MRF) for SAR image is proposed. The approach is firstly used to perform coarse segmentation in blocks. Then the image is modeled with simple MRF and adaptive variable weighting forms are applied in homogeneous and heterogeneous regions. As a result, the convergent speed is accelerated while the segmentati...     

Fast recursive algorithm for two-dimensional Tsallis entropy thresholding method

Recently, a two-dimensional (2-D) Tsallis entropy thresholding method has been proposed as a new method for image segmentation. But the computation complexity of 2-D Tsallis entropy is very large and becomes an obstacle to real time image processing systems. A fast recursive algorithm for 2-D Tsallis entropy thresholding is proposed. The key variables involved in calculating 2-D Tsallis entropy are written in recursive form. Thus, many repeating calculations are avoided and the computation complexity reduces to O(L2) from O(L4). The effectiveness of the proposed algorithm is illustrated by experimental results.     

Fuzzy c-means clustering based on spatial neighborhood information for image segmentation

Fuzzy c-means (FCM) algorithm is one of the most popular methods for image segmentation.However,the standard FCM algorithm is sensitive to noise because of not taking into account the spatial information in the image.An improved FCM algorithm is proposed to improve the antinoise performance of FCM algorithm.The new algorithm is formulated by incorporating the spatial neighborhood information into the membership function for clustering.The distribution statistics of the neighborhood pixels and the prior probability are used to form a new membership function.It is not only effective to remove the noise spots but also can reduce the misclassified pixels.Experimental results indicate that the proposed algorithm is more accurate and robust to noise than the standard FCM algorithm.     

基于分形理论和神经网络的红外图像分割算法

针对实现红外图像的分割,快速准确地检测出红外序列中的人造目标的需要,结合分形特征和Ko-honen神经网络的特点,提出了一种基于分形技术的图像分割算法。该算法利用自然背景和人造目标的不同分形特征检测目标,提出了包括分形维数在内的7个红外图像特征,结合神经网络的自组织学习能力来进行图像分割。给出了算法实现的具体步骤。仿真试验结果表明,该算法能有效地实现红外图像的分割。     

Multi-resolution image segmentation based on Gaussian mixture model

1. INTRODUCTION Image segmentation, which groups an image’s pixels into some homogeneous regions with respect to one or more characteristics such as gray-level, color and texture, is a basic and challenging problem in image processing. Many researchers have devoted their efforts to this problem and many segmentation algorithms have been proposed[1], histogram based thresholding algorithm, edge detection method and region growing and merging method for instance. Gaussian mixture model bas…     

Restoration of space-variant blurred image based on motion-blurred target segmentation

In imaging on moving target,it is easy to get spacevariant blurred image.In order to recover the image and gain recognizable target,an approach to recover the space-variant blurred image is presented based on image segmentation.Because of motion blur's convolution process,the pixels of observed image's target and background will be displaced and piled up to produce two superposition regions.As a result,the neighboring pixels in the superposition regions will have similar grey level change.According to the pixel's motion-blur character,the target's blurred edge of superposition region could be detected.Canny operator can be recurred to detect the target edge which parallels the motion blur direction.Then in the segmentation process,the whole target image which has the character of integral convolution between motion blur and real target image can be obtained.At last,the target image is restored by deconvolution algorithms with adding zeros.The restoration result indicates that the approach can effectively solve the kind of problem of space-variant motion blurred image restoration.     

基于迁移学习和注意力机制的伪装图像分割

不同于常规目标,伪装目标特征模糊、尺度信息复杂多变、检测和分割难度更高.在现有伪装数据集基础上,提出了一种结合迁移学习和有效通道注意力的UNet网络伪装图像分割方法.首先,针对伪装目标特征模糊难以有效提取的问题,在UNet的下采样和上采样过程中,引入一种有效通道注意力机制,在不增加网络参数的同时,提高有效区域的特征权重...     

Simulated annealing spectral clustering algorithm for image segmentation

The similarity measure is crucial to the performance of spectral clustering. The Gaussian kernel function based on the Euclidean distance is usual y adopted as the similarity measure. However, the Euclidean distance measure cannot ful y reveal the complex distribution data, and the result of spectral clustering is very sensitive to the scaling parameter. To solve these problems, a new manifold distance measure and a novel simulated anneal-ing spectral clustering （SASC） algorithm based on the manifold distance measure are proposed. The simulated annealing based on genetic algorithm （SAGA）, characterized by its rapid convergence to the global optimum, is used to cluster the sample points in the spectral mapping space. The proposed algorithm can not only reflect local and global consistency better, but also reduce the sensitivity of spectral clustering to the kernel parameter, which improves the algorithm’s clustering performance. To efficiently apply the algorithm to image segmentation, the Nystrom method is used to reduce the computation complexity. Experimental results show that compared with traditional clustering algorithms and those popular spectral clustering algorithms, the proposed algorithm can achieve better clustering performances on several synthetic datasets, texture images and real images.     

基于SNIC的双时相SAR图像超像素协同分割算法

针对面向区域的合成孔径雷达(synthetic aperture radar,SAR)图像变化检测方法中存在的双时相图像边缘和空间对应关系不一致的问题,提出了一种基于简单非迭代聚类(simple non-iterative clustering,SNIC)的双时相SAR图像超像素协同分割算法.首先,构造一幅包含双时相S...     

基于S-粗集的图像阈值分割方法

介绍了S-粗集的概念, 结合其动态迁移特性给出了可以适应复杂背景和含噪环境的图像S-粗集表示模型, 使静态目标可以将"不好"特性像素点迁移出去. 利用粗糙熵平衡目标和背景粗糙度对边界的影响, 提出一种更具适应性的 图像阈值分割算法. 为了适应离散点的迁移, 同时避免粒度大小的选择, 结合包含度概念给出了图像变精度S-粗集表示模型, 利用精度参数来 控制调节获取最佳分割阈值, 实现目标提取. 仿真实验表明, 所提出算法具有更好的图像分割效果.