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Edge preserved image enhancement using adaptive fusion of images denoised by wavelet and curvelet transform

机译:使用小波和Curvelet变换去噪的图像的自适应融合来增强边缘保留的图像

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摘要

In this paper, a novel approach is proposed which utilizes features of wavelet and curvelet transform, separately and adaptively, in 'homogeneous', 'non-homogeneous' and 'neither homogeneous nor non-homogeneous' regions, which are identified by variance approach. The edgy information that could not be retained by wavelet approach is extracted back from its residue by denoising it with curvelet transform. This extracted information is used as edge structure information (ESI) for fusing offshore regions of denoised images obtained by usage of wavelet and curvelet transform. The result of the image enhanced by such spatially adaptive fusion technique shows the improvement in the preservation of the edgy information. It also yields better smoothness in background (homogeneous region or non-edgy region) due to the removal of fuzzy edges developed during the denoising process by the curvelet transform.
机译:在本文中,提出了一种新颖的方法,该方法利用小波和curvelet变换的特征分别并自适应地在“均质”,“非均质”和“均质或非均质”区域中进行差异化,并通过方差方法进行识别。小波方法无法保留的前锋信息通过使用Curvelet变换进行去噪从残差中提取出来。该提取的信息用作融合通过使用小波和曲线波变换获得的去噪图像的离岸区域的边缘结构信息(ESI)。通过这种空间自适应融合技术增强的图像结果显示出在保存前卫信息方面的改进。由于通过Curvelet变换消除了在去噪过程中产生的模糊边缘,因此在背景(均匀区域或非前锋区域)中还可以产生更好的平滑度。

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