图像灰度级

288×4红外热像仪实时图像灰度级调整

Application of Real Time Image Gray Level Adjusting in 288 × 4 Thermal Imager

进一步应用统计法分析纹理特征，统计法的关键是计算灰度共生矩阵，它有3个参数：生成方向、生成步长、图像灰度级。

Using statistical analysis of texture features , you can find picture and image to match the picture library . The key is to calculate gray co-occurrence matrix . It has three parameters : the direction of generation , generation step , image gray level .

仿真结果表明，该方法的效率明显优于标准的FCM算去。最后，本文又基于SAR图像灰度级分布模型，提出了一种结合空间信息模糊域图像分割方法。

The simulation results show that the efficiency of the method is superior to the standard FCM algorithm . Finally , the paper is based on SAR image grayscale distribution model , this paper proposes a fuzzy domain image segmentation method combined with spatial information .

在此基础上，提出了图像灰度级有含义盲水印算法和基于DCT系数特性的盲水印算法，并通过一些常见的图像处理攻击实验验证了这两种算法生成水印的性能。企业形象研究；

By virtue of the study , a grayscale meaningful image blind watermarking algorithm and a blind watermarking algorithm based on the property of DCT coefficients are proposed . Then the design principles are simulated and performances are validated through some common attack experiments of images .

一种基于双阈值的实时图像灰度级压缩方法

A Method of Real-time Image Grayscale Compression Based Double Threshold

对图像灰度级分段的压缩编码

Compression code by segment to gray scale of image

直方图是图像灰度级的概率密度函数，它给图像提供了许多特征。

The histogram is the probability density function of the image level . It gives quite a few characteristics of the image .

灰度相关纹理分析法为消除图像灰度级不匹配对融合结果的影响，对待融合图像的灰度直方图进行了匹配处理。

The Gray Level Dependence Texture Analysis Approach in order to increase the spectral inherit , we make a histogram match in images to be fused .

这些算法的核心思想是假设边缘点对应于原始图像灰度级梯度的局部极值点。

The core idea of these algorithms is to assume that the edge points correspond to the original image gray-level gradient of the local extreme points .

该算法通过定义在图像灰度级上的测度，计算图像中每一个象素点的奇异性和它的多重分形谱，然后根据多重分形谱，提取图像的边缘信息。

Based on the measure of image grayscale , singularity of each pixel in the image and its multifractal spectrum are calculated , accordingly , the edge information of image is given .

在最大熵原则基础上利用条件迭代算法对图像灰度级进行最佳分类，对各分类区域进行相应的灰度变换，根据不同需要选取变换参数，在图像对比度增强同时各区域均衡性也得到很大改善。

According to the maximum entropy principle , the image gray levels were classified optimally by iterated conditional modes , and the transformation parameters were selected to enhance the image contrast and improve region homogenization .

提出了一种新的自适应阈值选择方法。该方法基于图像的灰度级特征，以前景和背景最大程度地分开为判据，定义了新的阈值识别函数来选择最佳的阈值，对图像进行分割。

A new adaptive threshold method for the image is presented according to making object and background separated completely .

为了较好地扩展增强后图像整体灰度级的动态范围，本文采用改进的对比度拉伸算法来进一步提高视频图像的对比度。

In order to expand the whole grayscale dynamic range of enhanced image , an improved contrast stretching algorithm is used to enhance video image contrast .

通过对灰度图像的灰度级压缩，将图像中每个像素的灰度值用一个合适的类标志来代替，构成一个类-图像。

Through quantized the image to several representing class , the image pixel values are replaced by appropriate color class labels , forming a class-map of the image . grade .

处理后的图像再经过灰度级转换，最后生成激光雕刻图像。

After processing , the image is going to do the conversion of gray degrees . At last , a laser-carving image is generated .

时域帧调制技术包含分屏子空间位权扫描和帧自耦合抖动算法，完成了数字图像显示高位灰度级的扫描驱动。

The time-domain frame modulation technique completed the digital image high-level gray-scale scan-drive , including multi-screen subspace scanning frame modulation and the self-coupling frame dithering algorithm .

为获取SAR图像，需要进行灰度级压缩并缩小图像，截取ROI以获得研究所需的一部分。

In order to get target SAR images , we should compress the gray-scale and size of images and then cut out ROI .

该方法利用图像直方图计算各灰度级下的Fisher评价函数值，其最大值即对应于最佳分割阈值。

In the new method , the image gray histogram is used to compute Fisher criterion function value of all gray grades , and the optimal threshold is determined at the maximum value of Fisher criterion function .

通过分析热红外图像的特点及图像灰度级与温度的关系，提出一种廉价的红外目标背景图像生成途经。

By analyzing the characters of hot infrared image and relation between grad-scale levels and temperature , the article proposes an inexpensive method to produce the background image of infrared target .

图像的分形维数能够表述图像空间纹理不同灰度级间的相关特性，是描述自然纹理图像的一个有用工具。

The fractal feature of image reflects the correlation between different gray 's grades of image texture .

在计算机视觉和图像处理中，边缘检测涉及到图像的灰度级发生重要变化的定位和导致这些变化的物理现象。

In computer vision and image processing , edge detection concerns the localization of significant variations of the grey level image and the identification of the physical phenomena that originated them .

利用JPEG方法对图像进行压缩，并采用直方图相交匹配函数求得图像灰度级的匹配程度。

The JPEG compress method was applied , and the histogram cross matching function was used to measure the matching degree in this research .

根据灰度压缩前后图像直方图间的形态差异，提出一种衡量各种合成孔径雷达（SAR）图像灰度级压缩算法性能的两步检验方法。

Based on the requirement that gray-scale compressed Synthetic Aperture Radar ( SAR ) image should preserve the distribution of original data , this paper evaluates the performance of gray-scale compression algorithms with a two-step method .

该方法将图像分为目标和背景，并分别建立相应的模糊隶属函数来描述图像各个灰度级属于目标和背景的模糊特性，进而给出图像模糊熵的描述。

The method defines different member function for the object and background of the image to transform the image into fuzzy domain with maximum fuzzy entropy .