嵌入式低内存SIMD处理器的脉冲噪声去除

Jong-Myon Kim, Soojung Ryu, A. Gentile, L. Wills, D. S. Wills
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引用次数: 6

摘要

矢量中值滤波器在保留图像细节的同时有效地降低了噪声。然而,它们对彩色图像的高计算复杂性使得它们在实时系统中不切实际。我们提出了新的计算效率高的过滤算法,称为索引映射过滤器(IMF)。这些滤波算法通过在大规模数据并行处理器阵列上实现而得到加速。除了更高的计算效率外,这些算法还可以对损坏的彩色图像进行鲁棒的降噪。对均方误差、信噪比和视觉比较指标的分析表明,IMF在校正彩色图像中的脉冲噪声方面与矢量中值滤波器(VMF)具有竞争力。这些算法是在SIMD处理器阵列上实现的,该处理器阵列是为高效率、高性能的便携式产品而开发的。在50mhz工作的4096节点SIMD芯片上执行,将IMF 3/spl times/3窗口应用于256/spl times/256彩色图像,索引映射距离滤波器(IMDF)需要442微秒(22104时钟周期),索引映射中值滤波器(IMMF)需要408微秒(20415时钟周期)。
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Impulse noise removal on an embedded, low memory SIMD processor
Vector median filters efficiently reduce noise while preserving image details. However, their high computational complexity for color images makes them impractical for real-time systems. We propose new computationally efficient filtering algorithms, called index mapping filters (IMF). These filtering algorithms are accelerated by implementing them on a massively data parallel processor array. In addition to greater computational efficiency, these algorithms result in robust noise reduction of corrupted color images. Analyses of mean square error, signal-to-noise-ratio, and visual comparison metrics indicate that IMF are competitive with the vector median filter (VMF) in their ability to correct impulse noise in color images. These algorithms are implemented on a SIMD processor array being developed for high efficiency, high-performance portable products. Executing on a 4096 node SIMD chip operating at 50 MHz, IMF 3/spl times/3 window applied to a 256/spl times/256 color image would take 442 microseconds (22104 clock cycles) for index mapping distance filter (IMDF) and 408 microseconds (20415 clock cycles) for index mapping median filter (IMMF).
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