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1)  Entropy image
熵图像
2)  image entropy
图像熵
1.
Color image segmentation and edge detection using Unit-Linking PCNN and image entropy
Unit-Linking PCNN和图像熵的彩色图像分割与边缘检测
2.
Based on the analysis,a new method was proposed for DAN estimation in spaceborne SAR imaging by finding the minimum of image entropy or the ma.
分析表明,基于图像均方差的DAN估计优于图像熵的DAN估计,前者在成像区域场景反差较大和较小时均适用,而后者在成像区域场景反差较小时表现不稳定。
3.
In order to solve this problem,the fast selection algorithm was proposed from different aspects: Firstly,for luminance mode selection,the method was proposed that utilizes the image entropy value to predict the mode of the macroblock,and updates the threshold adaptively by a sl.
针对亮度块的模式选择过程,提出了基于图像熵值和滑动窗口机制自适应地调整熵值阈值的方法对宏块模式进行预判;针对亮度模式中多个预测方向的选择,充分利用中间结果,预先排除一些可能性小的预测方向;在亮度块和色度块相结合的率失真统计中,改变算法结构,预先计算色度块最佳模式。
3)  entropy of the image
图像熵值
4)  local entropy of image
图像局部熵
1.
The property of local entropy of image and a novel method of infrared objects detecting based on local entropy of image were presented.
分析了图像局部熵的性质,提出了一种基于图像局部熵的红外图像分割方法。
5)  image entropy evaluation
图像熵评价
6)  image information entropy
图像信息熵
1.
According to the adaptive requirements of medical segmentation algorithm,the article introduced image information entropy algorithm based on the research on C-V model algorithm of the level set picture segmentation methods,solved the iterated parameters setting issue in the curve evolvement,and enhanced the adaptive capability of C-V model segmentation algorithm.
根据医学分割算法的自适应要求,在水平集图像分割方法C-V模型算法的研究基础上,引入图像信息熵算法,通过计算演化曲线内外的图像熵,解决曲线演化过程中迭代参数设定问题,达到增强C-V模型分割算法的自适应能力。
2.
Image information entropy describes the average information contents efficiently,but insensitive to point mutations.
讨论了天空中四类不同区域的图像信息熵。
3.
The capability of multi-focus image fusion is evaluated by calculating image information entropy and Root Mean Square Error(RMSE).
对多聚焦图像和多光谱彩色图像分别采用计算图像信息熵和均方根误差、计算图像平均梯度的方法对融合的性能进行评价。
补充资料:高光谱分辨率遥感图像及图像光谱信息提取


高光谱分辨率遥感图像及图像光谱信息提取


  高光谱分辨率遥感图像及图像光谱信息提取 郑兰芬供稿
  
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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