计算机与现代化 ›› 2013, Vol. 1 ›› Issue (5): 80-86,9.doi: 10.3969/j.issn.1006-2475.2013.05.019
• 图像处理 • 上一篇 下一篇
沈维燕，黄艳，张颖
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SHEN Wei-yan， HUANG Yan， ZHANG Ying
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摘要： 对于一幅观察到的图像，其特征不仅包含几何结构，而且可能包含纹理或者噪声。图像特征的分类与分割在图像处理和图像识别领域中起到重要作用（如去噪、边缘检测和纹理分割）。本文从函数空间和频域变换的角度，介绍图像特征描述方法现状，并进行比较，总结各自的优缺点，最后给出图像特征目前研究的应用领域。
关键词: 图像特征, 函数空间, 有界变差, 小波变换, 曲波变换
Abstract: An observed image which is characterized not only contains the geometric structure, but also may contain noise or texture. Image feature classification and segmentation play an important role in the fields of image processing and pattern recognition (such as de-noising, edge detection and texture segmentation). From the function space and frequency-domain transformation, this paper introduces the represent methods of image feature and compares it, summarizes the advantages and disadvantages of each. At the end, the application area of image feature study is given in personal opinion.
Key words: image feature, function space, bounded variation, wavelet transform, contourlet transform
中图分类号:
TP391.41
沈维燕;黄艳;张颖. 基于函数空间和频域的图像特征描述方法综述[J]. 计算机与现代化, 2013, 1(5): 80-86,9.
SHEN Wei-yan;HUANG Yan;ZHANG Ying. Overview of Represent Methods of Image Feature Based on Function Space and Frequency Domain[J]. Computer and Modernization, 2013, 1(5): 80-86,9.
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链接本文: http://www.c-a-m.org.cn/CN/10.3969/j.issn.1006-2475.2013.05.019
http://www.c-a-m.org.cn/CN/Y2013/V1/I5/80
