gray-level造句

• Public watermarking algorithm of gray - level still images combining dwt and dct
  小波和余弦变换相结合的灰度图像水印算法
• There are so many differences between binary images and the gray - level or color images
  二值图像只有黑白两种颜色，该类图像的信息隐藏不同于灰度及彩色图像。
• Therefore , there will be more challenge to realization fast recognising and tracing in chromatic image than in gray - level image
  由于彩色图像的信息量大，它比黑白图像目标的识别和跟踪问题具有更大的挑战性。
• In the end of the paper , the method is tested on 80 gray - level images and 44 color images which are selected from the stirling image database
  在最后，本文应用striling数据库中的80幅灰度图像和44幅彩色图像对本方法进行了测试。
• On this basis , the four numerical features identifying the content of image are raised from gray - level co - occurrence matrix of the image
  在此基础上，利用图像的灰度共生矩阵，统计出反应纹理一致性、纹理对比、纹理的熵和纹理相关性的数量值。
• The algorithms of image processing , including pixel gray - level detection , intensity transform , noise smoothness and image sharpen are discussed in detail
  本文详细的研究了图像处理的算法，实现了像素灰度提取、灰度变换、图像平滑、图像锐化等算法。
• Color image is the best approach to the world , as there are more advantages in color image processing than in gray - level image
  在各种光学图像中,彩色图像是对外部客观世界的最为逼近的描述,因此相比灰度图像来说,对彩色图像的处理可以获得更大的信息量。
• Next , this paper describes a new feature - based method using edge information of typical objects combined with local gray - level statistical information to image - to - image registration
  在此基础上，本文提出一种结合局部灰度信息与边缘形状信息的基于特征的sar图像配准方法。
• For the seaport targets detection , this thesis adopts a segmental method based on the gray - level and the gradient ; it works much better than the traditional method and is more suitable for parallelism
  在港口目标识别中，本文采用了一种基于灰度和梯度的分割方法，效果比传统方法好，更适于并行。
• The point of singular signal ' s conjoint pixel always changes acutely in its gray - level value . the gray - level distributing gradient of conjoint pixels can show this change
  而信号的奇异点或突变点往往表现为相邻像素点处的灰度值发生了剧烈的变化，我们可以通过相邻像素灰度分布的梯度来反映这种变化。
• In the pretreatment , we mend image by gray - level and direction - raph filtering . the program we proposed , without binarization and thinning , has high rapidity and saves a lot of calculation time
  预处理时，先对采集的指纹进行灰度滤波，然后再通过计算块方向图对指纹进行方向图滤波，从而实现灰度修补。
• A new image quality assessment criterion is suggested on the basis of the statistical features of the gray - level histogram of images to control the iterative procedure of the proposed image enhancement algorithm
  同时为了结束迭代增强，基于图像灰度直方图分布的统计特性，提出了一种客观的图像质量评价指标。
• On the base of i2 , the suitable threshold is found , and the gray - level edge image i1 is converted to binary edge image with this threshold . consequently , the edge extraction of color image is completed
  在i _ 2的基础上，采用最小误差方法求得分割阈值，并用该阈值对i _ 1进行二值化处理，从而完成彩色图像的边缘提取。
• Experiments on gray - level and color images show that it yields results with lower root - mean - squared errors and preserves better high - frequency details such as high contrast and sharp edges
  在灰度和彩色图像上的实验均表明该方法得到的结果具有更低的均方根误差，而且更好地保持了高频空间的细节，例如高对比度和锐利的边缘。
• Generally , it is difficult to extract and matching feature in high precision using classic registration method due to speckle noise and the complex distribution of gray - level in sar image
  由于sar图像相干斑噪声的影响和灰度分布的复杂性，利用传统方法作配准时一般面临特征提取和局部灰度匹配难度大、精度无法满足需要的困难。
• To deal with the problems mentioned above , a generalized iterative fuzzy enhancement algorithm is proposed in this thesis that consists of a three - stage procedure , i . e . , image filtering , fuzzy enhancement and gray - level transformation
  为了解决上述问题，本文在经典模糊增强方法和灰度变换基础上提出了一种广义的迭代模糊增强算法。
• In addition , a sophisticated mechanism derived from dwt coding is introduced to take into account several hvs phenomena such as gray - level sensitivity , noise sensibility around edges and isofrequency and nonisofrequency masking
  另外，引入了一个由dwt编码而来的复杂的机理来考虑几个hvs现象如灰度级敏感度、边缘噪音敏感度和频率掩蔽。