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首页> 外文期刊>Journal of Imaging Science and Technology >Additive Spatially Correlated Noise Suppression by Robust Block Matching and Adaptive 3D Filtering
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Additive Spatially Correlated Noise Suppression by Robust Block Matching and Adaptive 3D Filtering

机译：通过稳健的块匹配和自适应3D滤波来实现与空间相关的附加噪声抑制

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摘要

The evolution of modern sensors for image acquisition brings as much obstacles as many possibilities to obtain multidimensional data with high resolution and rich information. One of the most perceptible destructive factors in visual data is noise. Due to complexity of modern sensors and approaches to signal collecting or preprocessing, noise model becomes complicated. The article's goal is to introduce and solve a problem of suppressing additive spatially correlated noise (ASCN) which is present in images due to different sources and has various levels of correlation. It is shown that even modern filters attempting to suppress correlated noise often demonstrate unsatisfactory efficiency. Here we propose and analyze two modifications of 2D discrete cosine transform (DCT) based filter and the state-of-the-art BM3D technique. Both are based on accounting spatial spectrum of the noise by setting frequency-dependent thresholds. Furthermore, the modified BM3D filter exploits a similarity measure robust to noise spectrum in block matching. (C) 2018 Society for Imaging Science and Technology
机译：用于图像采集的现代传感器的发展为获得高分辨率和丰富信息的多维数据带来了尽可能多的障碍。视觉数据中最明显的破坏性因素之一是噪声。由于现代传感器的复杂性以及信号收集或预处理的方法，噪声模型变得复杂。本文的目的是介绍并解决抑制由于空间原因而在图像中出现且具有各种相关级别的加性空间相关噪声（ASCN）的问题。结果表明，即使是试图抑制相关噪声的现代滤波器也常常表现出不令人满意的效率。在这里，我们提出并分析了基于2D离散余弦变换（DCT）的滤波器和最新BM3D技术的两种改进。两者都基于通过设置频率相关阈值来考虑噪声的空间频谱。此外，改进的BM3D滤波器在块匹配中采用了对噪声频谱鲁棒的相似性度量。 （C）2018影像科学与技术学会

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