Hardware architecture dedicated for arithmetic mean filtration implemented in FPGA

P. Malík
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引用次数: 1

Abstract

An FPGA-based hardware architecture for arithmetic mean filtration optimized with 49-pixel square neighborhood is proposed. The arithmetic mean formula is optimized and transformed into the new formula that introduces the computational cyclic sequence which results in multiplication-less process with only 9 additions necessary for each pixel. The external memory is used to save partial results but the memory requirement has been optimized so the requirement is the same as for the input data. This proposed architecture is oriented to security tracking applications; however, it can be used in any image processing applications that use arithmetic mean filtering. It is resolution and frame rate independent and suitable for all high resolution and multiple camera systems. FPGA optimization made it also suitable for FPGA-based reconfigurable systems and computing.
专用于算术平均滤波的硬件架构在FPGA上实现
提出了一种基于fpga的49像素方形邻域优化算法平均滤波硬件架构。对算术平均公式进行了优化,并将其转化为新的公式,该公式引入了计算循环序列,使得每个像素只需要9个加法,无需乘法。外部内存用于保存部分结果,但内存需求已经优化,因此需求与输入数据相同。提出的体系结构面向安全跟踪应用;然而,它可以用于任何使用算术平均滤波的图像处理应用。它与分辨率和帧率无关,适用于所有高分辨率和多摄像机系统。FPGA优化使得它也适用于基于FPGA的可重构系统和计算。
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