We have recently proposed approximate median filters (APMFs). They are based on the sorting network and achieve acceptable image quality under low-cost hardware. In this brief, we develop a specific comparator to improve the capabilities of those filters in noise elimination. The architecture of our inexact median filters (IMFs) is regular and modular. Also, we introduce the histogram-based error dispersion plot as a new error evaluation method to have a better assessment of IMF performance. Simulation results show that the proposed filter is effectively low cost in power, area, and speed. Despite the tradeoff between the filtering accuracy and circuit characteristics, the output quality of the filter is largely similar to that of the precise one. Also, the degradation is almost not noticeable to the human eye.

中文翻译：

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一种用于去除灰度图像中椒盐噪声的改进的不精确算术中值滤波器

我们最近提出了近似中值滤波器 (APMF)。它们基于排序网络，并在低成本硬件下实现可接受的图像质量。在本简报中，我们开发了一个特定的比较器来提高这些滤波器在噪声消除方面的能力。我们的不精确中值滤波器 (IMF) 的架构是常规和模块化的。此外，我们引入了基于直方图的误差分散图作为一种新的误差评估方法，以更好地评估 IMF 的性能。仿真结果表明，所提出的滤波器在功率、面积和速度方面都有效地降低了成本。尽管在滤波精度和电路特性之间进行权衡，但滤波器的输出质量与精确滤波器的输出质量基本相似。此外，人眼几乎察觉不到这种退化。