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- LLL image noise 微光图像噪声
- A LLL image simulation scheme is proposed oriented to daytime aerial image. 并在此基础上,提出了基于日间航拍图像的微光图像仿真方案。
- LLL image simulation scheme is proposed oriented to daytime aerial image. 并在此基础上，提出了基于日间航拍图像的微光图像仿真方案。
- Image noise removal by PDEs model is an effective tool. 应用偏微分方程进行图像去噪是一种有效的工具。
- In the second chapter, the principle, characteristics, types and parameters of LLL image intensifier are introduced. 第二章介绍了微光像增强器的原理、特性、种类及性能参数。
- A data analysis process that increases image clarity and removes image noise. 一种提高图象清晰度、除去图象噪声的数据分析方法。
- In the second chapter, the principle, characteristics, types and parameters of LLL image intensifier are introduced. The measurement principle and methods about parameters are also emphasized. 第二章介绍了微光像增强器的原理、特性、种类、性能参数及其相应的测试原理和方法。
- While the traditional Gaussian Filter can reduce image noise; it may also blur image edges. 传统的高斯滤波在去除图像噪声的同时产生了边缘模糊的问题。
- Based on the principle of the single channel photon counting technique, the measurementprinciple, method, equipment, experiment and resultS of the EBI of LLL image photon counting intensifier are proposed. 在论述单通道光子计数技术原理的基础上，提出了微光图像光子计数器像管等效背景的测试原理、方法、装置、实验及结果。
- Note: Image noise reduction, JPEG artifact removal and crisp image magnification tool. 一款图像处理软件,可以用来去掉图片上的痕迹和无失真放大。
- In the field of digital image processing, image compressing, image amplifying and image noise diminution based on DWT have a good practical effect. 由于小波变换的良好特性，使其在众多实际应用中都能得到很好的应用，并取得比原有技术更好的实际效果。
- At last, the assessment method of the degression of image enhancement algorithm on image noise is proposed. 而经过5帧平均算法后的图像质量明显改善，对比度增加。
- It is very important to design practical and real-time processing hardware systems, which can be applied to both infrared and LLL images. 针对红外图像和微光图像的不同噪声特点，设计实用、实时的噪声处理系统显得十分重要。
- Image noise and grain artifacts were present in lung apexes above the level of the aortic arch and lung bottom below the midriff. 图像噪声明显、颗粒较粗大主要出现在主动脉弓以上肺尖区域和膈顶以下背侧区域。
- Experimental results show that this four step pretreatment method can eliminate image noise and reduce brightness difference effectively. 实验结果表明，此方法可以有效地去除图像的噪声，平衡立体图对间的亮度差异。
- Filtering coefficient is obtained by the simplified self-adaptive model and DSI image noise reducer is designed and implemented. 用简化自适应滤波算法确定滤波系数，设计和实现了DSI序列图象的动态降噪，并抑制了快变图象的拖影，具有较好的动态跟踪效果。
- Discuss the effect of algorithm statistic features, the influences of image noise, and the reason for low efficiency of steganalysis algorithms. 对统计特征提取的有效性、图像噪声对检测的影响、导致检测效率降低的原因进行了分析。
- Firstly,the inner product energy of image points is introduced,which not only can enhance line edges but also restrain image noise and non-line edges. 首先,引入图像点的内积能量运算,该运算不但能有效地增强直线边缘,而且还具有抑制噪声和非直线边缘的能力。
- The more information of original image is used in removing image noise, the better will the effect of filter be, but this is usually impossible or impracticable. 摘要图像滤噪时，利用原图像的信息越多滤波效果越好，但这通常是不可行的或不可能的。
- By means of wavelet transform, the image detail information can be preserved while image noise being removed, but image edge information can also been smoothed. 摘要应用小波变换去除图像噪声时虽然能保持图像的细节信息，但是图像的边缘信息被平滑了。
