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Multi-level adaptive switching filters for highly corrupted images

机译：用于高度损坏图像的多级自适应切换滤波器

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The performance of a switching filter is highly dependent on its detection accuracy. Inspired by adaptive median filter methodology, this paper proposes a multi-level adaptive switching filter (MASF) for the recovery of highly corrupted images. In particular, the adaptive technique is employed in all the detective, edge-preserving and restorative stages in order to improve noise discrimination and suppression simultaneously. Most critical design parameters in the proposed algorithm, e.g., the limit of window-expansion size and the noise range, are self-adaptive so as to retain simple implementation and high computational efficiency. Furthermore, several effective modifications on both stages of the MASF, such as the convergence factor, switching initialization and spatial adaptive weighting, are also introduced in order to provide better and more robust results. Monte-Carlo simulations show that the MASF outperforms many existing state-of-the-art algorithms in terms of both visual and quantitative results. (C) 2015 Elsevier Inc. All rights reserved.
机译：开关滤波器的性能在很大程度上取决于其检测精度。受自适应中值滤波器方法的启发，本文提出了一种多级自适应切换滤波器（MASF），用于恢复高度损坏的图像。特别地，在所有侦探阶段，边缘保持阶段和恢复阶段中都采用自适应技术，以便同时改善噪声识别和抑制。所提出的算法中最关键的设计参数，例如窗口扩展大小的限制和噪声范围，是自适应的，从而保持简单的实现和较高的计算效率。此外，还对MASF的两个阶段进行了一些有效的修改，例如收敛因子，切换初始化和空间自适应加权，以提供更好和更可靠的结果。蒙特卡洛模拟显示，就视觉和定量结果而言，MASF均优于许多现有的最新算法。 （C）2015 Elsevier Inc.保留所有权利。

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