Adaptive trimmed averaging filter for noise removal in color images

B. Smolka, Krystian Radlak
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引用次数: 1

Abstract

In the paper a novel filtering design intended for the removal of mixed impulsive and Gaussian noise contaminating color images is proposed. The new denoising scheme is based on the concept of the robustified vector median, which determines the center of a cluster of most similar pixels. The filter output is the average of pixels belonging to the cluster and thus it can be treated as an adaptive trimmed averaging filter. The new filtering design is capable of suppressing mixed impulsive and Gaussian noise, while preserving and even enhancing image edges. The experiments revealed that the new noise reduction design outperforms the standard trimmed vector median and other state-of-the-art methods. The simplicity of the proposed filter and its low computational load enables its applications in real time image and video enhancement applications.
用于彩色图像去噪的自适应裁剪平均滤波器
本文提出了一种新的滤波设计,用于去除干扰彩色图像的脉冲和高斯混合噪声。新的去噪方案基于鲁棒化向量中值的概念,它确定了最相似像素的聚类的中心。滤波器输出是属于集群的像素的平均值,因此它可以被视为自适应修剪平均滤波器。新的滤波设计能够抑制混合脉冲和高斯噪声,同时保持甚至增强图像边缘。实验表明,新的降噪设计优于标准的裁剪向量中值和其他最先进的方法。所提出的滤波器的简单性和低计算负荷使其能够应用于实时图像和视频增强应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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