| 1. | Ega enhanced graphic adapter
增强图像适配器 |
| 2. | This method can effectively remove the noise , enhance image mean grads and improve image visual effect
该方法可以有效地去除噪声，增强图像的平均梯度，改善图像的视觉效果。 |
| 3. | Now , there are many methods of image enhancement , but they will more or less bring bad effects when enhancing images
现有的图像增强方法有很多种，但它们在增强图像的同时，往往会带来了比较严重的负效应。 |
| 4. | Experiment result shows that this algorithm avoids over - enhancement of noise while enhancing image details with good visual effect
实验结果表明，该算法可以有效地增强图像的细节信息，减小噪声的增强幅度，改善图像的视觉效果。 |
| 5. | Image enhancement is an important part of image preprocessing , and enhanced images suitable for different applications can be obtained using different image enhancement methods
图像增强是图像预处理的重要组成。通过不同的图像增强手段可以得到适用于不同用途的增强图像。 |
| 6. | I n order to enhance image edges of different levels at the same time , we prese nt a multi - level fuzzy enhancement algorithm , and its fast computing algorithm is also given in t his paper
为了同时增强图像中不同灰度层次的边缘信息，提出一种多层次模糊增强算法，并且给出了快速实现算法。 |
| 7. | The both two methods use the local information of image , and overcome the shortcomings that process all of pixels by the same scale . the two methods have some difference
两种方法的共同之处在于：利用图像局部信息，克服了对每个像素采用相同尺度变换处理带来的缺点，最终得到了良好的增强图像。 |
| 8. | In this paper , firstly the micro - areas image acquisition is introduced . secondly , in order to enhance the useful characteristic , the image pre - processing is taken by histogram equalization and modified median filter
论文首先实现了微区图像的采集，为了增强图像的有用特征，采用灰度级修正和噪声抑制的方法对图像进行了预处理。 |
| 9. | This method was divided into 4 steps : wiping out random noise by mean filter , reducing gaussian noise by gaussian filter , balancing brightness difference between stereo image pair through histogram equalization , and enhancing image edges and details by laplace sharpness
此方法分为4个阶段：用均值滤波去除随机噪声；用高斯滤波去除高斯噪声；用直方图均衡化法平衡立体图对间的亮度差异；用拉普拉斯锐化增强图像的边缘和细节。 |
| 10. | After an image is decomposed , its edges , details and noise will exist in high frequency . noise can be removed by wavelet de - noising , and edges and details can be enhanced in high frequency , hence the goal of enhancing and de - noising at the same time can be attained
由于图像进行小波分解后，其边缘细节与噪声都存在于高频部分，因此，在高频段利用现有的小波去噪方法去掉噪声，增强图像中的边缘细节，从而达到同时实现去噪和增强的目的。 |
