1) image base
图像基
1.
The micro-elements of an iris image are analyzed by various image base functions and it is determined that the LoG function is the base function dominating iris image generation.
采用不同的图像基函数分析虹膜图像的基本微观结构,从而确定主导虹膜图像产生的图像基为LoG函数,进而利用LoG函数在多尺度空间检测虹膜细节特征。
2) image-based
基于图像
1.
Fast face detection combine both feature-based and image-based approach;
基于特征和基于图像相结合的快速人脸检测
2.
In this paper, we describe an image-based rendering technique called Inverse Concentric Mosaics (ICM) which is based on Concentric Mosaics (CM) .
阐述了“逆向同心拼图”技术 ( inverse concentric mosaics,简称 ICM) ,ICM是一种基于图像的绘制技术 ,是“同心拼图”技术 ( concentric mosaics,简称 CM)的一种扩展。
3.
In recent years, we can seen clearly the trend of increasing number of researchers\' interest in image-based modeling technology for its advantages of low-cost, relatively fast speed of modeling.
近年来,基于图像的建模技术以其成本低、建模速度相对较快得到越来越多研究者的关注,从单幅图像建模更因其简单、方便处理等优点得到较快的发展。
3) basic image
基本图像
1.
A new fast two dimension 8×8 Inverse Discrete Cosine Transform(IDCT) algorithm based on Look-Up Table(LUT) is presented,in which,the LUT structure is based on the DCT basic images.
提出一种基于查表法的二维8×8离散余弦逆变换(2D 8×8 IDCT)的快速算法,其查找表LUT(Look-UpTable)结构的设计是基于二维8×8 DCT的基本图像。
2.
The specialities of the basic images of the discrete cosine transform (DCT) and the characteristics of the data of the practical images are discussed, and a fast algorithm for computing 8×8 two-dimensional IDCT is presented in this paper.
讨论了离散余弦变换(DCT)的基本图像的特性以及实际图像数据的特点,提出了利用基本图像进行二维8×8离散余弦逆变换(IDCT)的快速算法。
3.
The new algorithm is based on the conception and symmetry of basic images.
基于基本图像的概念及其对称性,提出一种计算二维8×8离散余弦变换(DCT)量化后系数的查表快速算法。
4) basic image
基图像
1.
Then the basic images of template image are presented and an image is expressed with the linear combination of the basic images.
首先证明了图像的大量信息主要体现在图像矩阵奇异值分解的前几个最大奇异值所对应的左、右奇异向量中,然后给出了模板图像的基图像,并将图像展开成基图像的线性表示,提取其组合系数作为图像的代数特征并用于人脸识别中。
2.
NMF is applied to the each group’s images to obtain the non-negative subspace constructed by basic image of each group’s images,project the training images and testing images to each feature subspace.
将训练图像分组,分别对每组图像作NMF,获取每组图像的基图像构成的非负特征子空间,将训练图像和测试图像分别向各个特征子空间进行投影,将每组图像提取出的特征系数混合,根据最近邻原则进行识别。
5) gene image
基因图像
6) graphic based
图像基准
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。
参考词条