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Energy-Efficient Gaussian Filter for Image Processing Using Approximate Adder Circuits

机译:使用近似加法器电路的可节能高斯滤波器进行图像处理

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This paper proposes the use of approximate adder circuits for 3×3 and 5×5 Gaussian filter implementations. The Gaussian filter is a convolution operator which is used to blur images and to remove noise, whose convolution implementation can be designed in hardware using only shifts and addition operations. In this work we evaluate the levels of approximations in computing or loss of accuracy in the arithmetic dataflow that the Gaussian filter can tolerate for a set of eight images. Our work deals with different levels of approximation in Ripple Carry Adders (RCA) which are part of the Gaussian filters adder tree implemented in hardware, and later compared to the best precise implementation of the same filter. Our results show an average energy savings of up to 40% and 25% for the approximate 3×3 and 5×5 Gaussian filters, respectively, without compromising the overall filtered images quality.
机译:本文提出使用近似加法器电路3×3和5×5高斯滤波器实现。高斯滤波器是一种卷积运算符,用于模糊图像并去除噪声,其卷积实现可以仅在硬件中使用换档和加法操作设计。在这项工作中,我们在算术数据流中评估计算或准确性损失的近似水平,即高斯滤波器可以容忍一组八个图像。我们的工作涉及纹波携带添加剂(RCA)中的不同级别的近似,它们是在硬件中实现的高斯滤波器的一部分,后来与同一滤波器的最佳精确实现相比。我们的结果分别显示平均节能高达40%和25%,分别为3×3和5×5高斯滤波器,而不会影响整体滤波图像质量。

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