计算机科学 ›› 2020, Vol. 47 ›› Issue (6A): 226-229.doi: 10.11896/JsJkx.200160009

• 计算机图形学 & 多媒体 • 上一篇    下一篇

一种基图像提取和内容无关图像重构方法研究

蓝章礼, 申德兴, 曹娟, 张玉欣   

  1. 重庆交通大学信息科学与工程学院 重庆 400074
  • 发布日期:2020-07-07
  • 通讯作者: 申德兴(493211790@qq.com)
  • 作者简介:lzl17309@126.com
  • 基金资助:
    重庆市教委科学技术研究项目(KJQN201800716)

Content-independent Method for Basis Image Extraction and Image Reconstruction

LAN Zhang-li, SHEN De-xing, CAO Juan and ZHANG Yu-xin   

  1. School of Information Science and Engineering,Chongqing Jiaotong University,Chongqing 400074,China
  • Published:2020-07-07
  • About author:LAN Zhang-li, born in 1973, Ph.D, professor, master supervisor, is a member of China Computer Federation.His main research interests include informatization and intelligentization of transportation, solar energy and image processing.
    SHEN De-xing, born in 1994, postgra-duate.His main research interest include image processing and so on.
  • Supported by:
    This work was supported by ProJect of Science and Technology Research Program of Chongqing Education Commission of China (KJQN201800716).

摘要: 图像作为一种典型信号,理论上可由一系列基本信号构成。为寻找一组可重构图像的基本信号,提出了基于特征的基图像提取和重构方法,使得可由任意图像集进行基图像提取并可由提取的基图像重构内容无关的任意图像。使用特征提取算法从训练集图像中分解出一系列基图像,阐述了基图像分解和提取的算法流程,通过将测试集图像投影到k个基图像构成的空间中得到投影系数,建立由投影系数和基图像重构原图像的方法和过程。实验结果表明,通过控制基图像数量k,图像的重构误差和质量可以达到较高要求,基图像的提取和重构的图像具备内容无关性,同时,该方法对于图像抽象特征的理解、深度神经网络应用等具有重要作用。

关键词: 基图像, 内容无关, 特征提取, 特征向量, 图像重构

Abstract: As one kind of typical signals,an image can theoretically be composed of a series of basic signals.In order to find a set of basic signals to reconstruct images,a method for obtaining basis images based on feature extraction and reconstructing images from them is proposed.It makes possible to obtain the basis images from any set of images and to reconstruct images from the obtained ones because it is content-independent.The algorithm flow of extracting a series of basis images from the training set of images by feature extraction algorithm is described.The system of reconstructing the original image from the proJection coefficient and basis images by proJecting the set of test images into the space formed by the k basis images is developed.The experimental results show that,by controlling the number of basis images,the error and quality of reconstucted images can achieve higher requirement,and the method for basis images extraction and image reconstruction is content-independent.At the same time,this method plays an important role in the understanding of abstract features of images and the deep neural network.

Key words: Basis image, Content-independent, Feature extraction, Feature vectors, Image reconstruction

中图分类号: 

  • TP301
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