一种新的基于内容遥感图像检索的图像分块策略

A New Image Decomposition Method for Content-Based Remote Sensing Image Retrieval

  • 摘要: 对常用的图像分块方法进行了说明,提出了平均块覆盖率、冗余数据比率等概念,以及平均块覆盖率和冗余数据比率是衡量CBRSIR系统分块方法优劣的重要标准这一论断。在此基础上,针对Quin-树存在的主要问题,提出了一种新的分块策略———Quin+-树,并将Quin+-树和Quad-树、Quin-树和Nona-树进行了分析和比较。实验证明,Quin+-树是最实用可行的CBRSIR图像分块方法。

     

    Abstract: Firstly,the ordinary image decomposition method are listed: Quad-tree,Quin-tree and Nona-tree,then these methods are analyzed and compared,and the concepts of average block cover ratio and redundant data ratio are proposed.On the basis of these,a judgment is made that the average block ratio and redundant data ratio are the most important standards to estimate the decomposition quality,the improve room of Quin-tree is discovered.Then,a new block-method,Quin~(+)-tree is proposed.Lastly,a remote sensing image A,1 024 pixels width by 1 024 pixels height is chosem and decompose by Quad-tree,Quin-tree,Quin~(+)-tree and Nona-tree by three levels.From five different aspects,these four image decomposition methods' results are analyzed and compared.

     

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