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An improved three-dimensional block matching image de-noise algorithm and its application in a 3D imaging sonar

机译:一种改进的三维块匹配图像降噪算法及其在3D成像声纳中的应用

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There are urgent needs for sonar image processing technology since sonar images generally have characteristics of low resolution and a weak target shielded in a strong reverberation background. A three-dimensional block matching image de-noise algorithm was used to suppress the speckle noise in SAS imaging processing. It usually adopts adjacent sub-blocks of the image for 3D transformation, and attains image de-noise by processing in the transform domain. Furthermore, we now face the challenge of three-dimensional image processing in a kind of 3D sonar, and there are already abundant azimuth sections of three-dimensional images available to be studied. There are more similar characteristics amongst different azimuth sections of 3D images than there are amongst adjacent sub-blocks of conventional image. Thus, an improved three-dimensional block matching image de-noise algorithm is proposed for 3D sonar image processing, in which the effectiveness of image de-noise are produced by ensemble average and transform domain processing. Its application in the 3D imaging sonar is also described in this paper. And because of the greater quantity of elements and greater similarity amongst sub-blocks, the image processing results show that the background noise is being properly suppressed.
机译:迫切需要声纳图像处理技术,因为声纳图像通常具有低分辨率和在强混响背景下被屏蔽的弱目标的特性。在SAS成像处理中,使用三维块匹配图像去噪算法来抑制斑点噪声。它通常采用图像的相邻子块进行3D变换,并通过在变换域中进行处理来实现图像降噪。此外,我们现在面对一种3D声纳中的三维图像处理的挑战,并且已经有大量的三维图像方位角部分可供研究。在3D图像的不同方位角部分中,比在传统图像的相邻子块中具有更多相似的特性。因此,提出了一种改进的三维块匹配图像降噪算法,用于3D声纳图像处理,通过整体平均和变换域处理来产生图像降噪的有效性。本文还介绍了其在3D成像声纳中的应用。并且由于子块中元素的数量更大并且相似性更高,所以图像处理结果表明背景噪声得到了适当的抑制。

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