提出了一种新的有效的图像阈值分割算法。本算法将小波理论，模糊集理论和信息论三者有机的结合起来。
A new effective image segmentation algorithm Based on Wavelet Operator is presented, which is tied tightly in Wavelet analysis with Fuzzy, information theory.
实验表明，改进的APEX算法能够有效应用在多种真实模糊图像上，增强图像对比度和锐化图像细节，使图像的视觉效果得到明显改善。
The improved APEX method could be usefully applied to a wide variety of real blurred images and enhanced contrast and sharpened structural details, leading to noticeable improvement in visual quality.
在常用的方法中，基于区域灰度平均的算法使图像模糊，而基于样条插值的算法计算耗时。
In the common methods, the algorithm based on the average of region gray makes image blur, and the algorithm based on spline interpolation wastes time.
仿真结果表明：该算法具有较强的检测模糊边缘能力，是一种实用、高效的边缘提取算法，同时此方法很容易扩展到多阈值图像边缘处理。
Simulation results show that: the algorithm is a practical and efficient edge detection algorithm, and this method can easily extend to more threshold edge detection of image processing.
结合中值与模糊滤波技术，提出了一种新的图像混合噪声滤波算法。
A new algorithm of mixed noise removal for digital image is presented combing median filter and fuzzy technology.
本文给出了模糊聚类算法在图像分割中的应用结果。
In this paper, the application of suppressed fuzzy clustering algorithm in image segmentation is introduced.
为解决由于相机高速运动而导致的图像模糊，利用定点DSP芯片TMS320C 6416和维纳滤波算法实现电子稳像。
To absolve image blur for high speed camera, fixed-point DSP TMS320C6416 and wiener filtering algorithm were adopted.
结果模糊K- 均值聚类算法能很好地分割出磁共振颅脑图像中的灰质、 白质和脑脊液。
Results Fuzzy K means clustering algorithm can segment white matter, gray matter and CSF better from the MR head images.
模糊聚类算法(FCM)应用于数字图像的边缘检测已取得了较好的效果。
Fuzzy c-clustering algorithm (FCM) is a useful tool in edge detection of digital image.
论文采用了一种基于改进的模糊C均值算法来聚类图像。
This paper proposes a modified fuzzy C-means (MFCM) clustering algorithm to cluster all images before retrieval.
为了提高超谱图像分类的精度，提出了模糊最大似然分类算法。
In order to improve the classification accuracy of hyperspectral images, a fuzzy maximum likelihood classification method is proposed.
提出了一种基于模糊免疫网络算法对火焰数字图像进行分类的研究方法。
The method based on fussy immune network algorithm was presented, by which the flame digital images can be classified better.
由于原始的模糊c -均值聚类算法没有考虑图像的空间信息，算法对图像中的噪音点十分敏感。
Without considering the spatial information of images, the original fuzzy C-means algorithm is very sensitive to image noise.
本文提出了一种基于知识的遥感图像模糊分类算法，在传统的模糊分类方法中加入了从GIS数据库中发现的知识，用它来辅助进行遥感图像分类。
In this paper, a knowledge-based fuzzy image classification method is proposed. In the method, knowledge discovery from GIS is introduced in to assist fuzzy image classification.
通过对焊缝图像进行广义模糊增强处理表明，该算法在增强对比度同时又可较好保持边缘。
Using this algorithm to dealing with weld image, the contrast ratio can be improved and the edges can be preserved well.
最后采用几幅不同的图像进行实验，结果表明该方法可行有效，并且对于模糊图像，算法也能获得满意的结果。
Using some images in experiment, the results show this method is feasible and efficient, and fits for fuzzy images too.
针对图像混合噪声提出了一种新型的模糊加权均值滤波算法。
A new efficient fuzzy weighted mean filter approach to the restoration of images corrupted by mixed noise was proposed.
针对最大熵阈值分割算法的计算缺陷，提出了一种基于直方图的模糊最大指数熵阈值图像分割新算法。
To overcome the defects of image segmentation by maximum entropy, a new method of image segmentation was presented by using fuzzy maximum exponential entropy based on histogram.
本文建立模糊马尔可夫场模型，并提出基于模糊马尔可夫场的图像分割新算法。
A fuzzy Markov random field (FMRF) model is established and a new algorithm based on FMRF for image segmentation proposed in this paper.
该文根据FCM算法和灰度图像的特点，提出了一种适用于灰度图像分割的抑制式模糊C -均值聚类算法(S - FCM)。
In the paper, a suppressed fuzzy c-means (S-FCM) algorithm, for intensity image segmentation, is proposed on the basis of the characters of FCM algorithm and intensity images.
针对内窥镜图像恢复的需求，结合模糊先验辩识算法和遗传寻优的思想给出了一种基于模糊遗传算法的图像恢复算法。
In light of the need to resume the endoscope image, a new algorithm is put forward, which combines the fuzzy experience-oriented identification algorithm and the idea of hereditary optimization.
目的介绍一种动态模糊聚类算法并利用该算法对磁共振图像进行分割研究。
Objective to introduce a dynamic fuzzy clustering algorithm and use it to do the study of segmentation of the brain in MRI.
本文分析了模糊矢量量化(FVQ)图像编码的原理，提出了一种指数型模糊学习矢量量化算法(EFLVQ)。
The principle of fuzzy vector quantization (FVQ) for image coding is discussed in this paper, and an exponential fuzzy learning vector quantization algorithm (EFLVQ) is proposed.
本文分析了模糊矢量量化(FVQ)图像编码的原理，提出了一种指数型模糊学习矢量量化算法(EFLVQ)。
The principle of fuzzy vector quantization (FVQ) for image coding is discussed in this paper, and an exponential fuzzy learning vector quantization algorithm (EFLVQ) is proposed.
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