传统的直方图均衡和灰度变换增强算法，不能针对红外图像的目标进行有效地增强。
Traditional histogram equalization and gray-scale transformation algorithms can't realize the enhancement of the target in the infrared image effectively.
分析了传统灰度图像直方图均衡化算法的不足，讨论并实现了一种改进的直方图均衡化图像增强算法。
A modified algorithm of histogram equalization to gray image manipulation was discussed and actualized by analyzing principia and deficiency of the traditional algorithm of gray image.
此文主要研究用于增强图像的灰度变换方法，包括线性灰度变换、非线性灰度变换与直方图均衡化方法。
This paper mainly tells us the ways of image gray transformation, including linear gray transformation, nonlinear gray transformation and the approach of histogram equalization.
直方图均衡可以使图像灰度分布接近均匀，提高图像对比度，但图像的信息量会有一定程度的损失。
The histogram equalization can enhance the contrast by redistributing the gray levels, it has the drawback that it reduces the information in the processed image.
说明：MF C实现灰度图像的各种点运算，如图像反色，窗口变换，线性变换，阈值变换，灰度均衡等。
MFC to achieve a variety of gray-scale image point operations, such as anti-color images, the window transform, linear transformation, threshold transform, gray balance, etc.
针对这一情况，将直方图均衡和灰度拉伸相结合，增强牌照图像，使图像更加清晰。
Aiming at this problem, histogram equalization and gray stretch are used to enhance license plate image, and make the image clearer.
传统的图像增强方法有灰度变换、直方图修正、直方图均衡、图像平滑和维纳滤波。
The traditional image enhancement approaches include gray-scale transformation, histogram modification, histogram equalization, image smoothing and Wiener filtration.
第三步，为了减轻光线不均匀对灰度图像造成的影响，对产品图像进行灰度直方图均衡；
Third, the gray-level histogram of image is equalized in order to reduce the influence of uneven light to the gray-level image.
利用自开发软件，对图像进行灰度变换和直方图均衡化处理后，采用频域同态滤波的方法对图像进行降噪滤波处理。
After the gray transformation and the histogram equalization, these images were filtered by a frequency-domain homomorphic filter, hence noises in the images were greatly reduced.
该算法基于图像的特点，利用K均值聚类算法将图像分成几个灰度区间，然后再分别进行均衡化。
According to the characters of the images, the algorithm separated image into several regions by K-means clustering algorithm, and each region is equalized respectively within their gray levels.
采用图像去噪、灰度变换、直方图均衡化以及非均匀背景修正技术等提高了原始图像成分的清晰度，使图像变得更便于计算机分析和处理。
The use of image denoising, gray-scale transformation, histogram equalization, and uneven background correction techniques make the image more easily processed and analyzed.
在对比指纹图像的灰度直方图增强的技术的基础上，针对均衡化算法的不足和现有直方图规定化算法中映射规则计算量大的情形，提出一种改进的规定化算法。
In view of the shortcoming of direct histogram equalization and big work of mapping law's calculate in histogram specification, proposed one kind of improvement stipulation algorithm.
指纹预处理一般包括以下几个步骤：图像质量评估、均值滤波、灰度归一化、灰度均衡化、方向滤波、二值化以及细线化。
Image preprocessing is usually consisted of following steps: quality assessment, mean filtering, gray normalization, gray equalization, the Oriental filtering, binarization as well as thinning.
首先对彩色图片进行灰度化，再采用直方图均衡化的方法来进行图片的预处理，以获得比较好的图像拼接效果。
First carries on the gradation to the colored picture, again USES the histogram equalizing the method to carry on the picture the pretreatment, obtains the quite good image splicing effect.
该算法基于图像的特点，利用K均值聚类算法将图像分成几个灰度区间，然后再分别进行均衡化。
The complexity of time and spatial is becoming the difficulty of K-Means clustering algorithm while it deals with the huge amounts of data sets.
该算法基于图像的特点，利用K均值聚类算法将图像分成几个灰度区间，然后再分别进行均衡化。
The complexity of time and spatial is becoming the difficulty of K-Means clustering algorithm while it deals with the huge amounts of data sets.
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