韩玉鑫,王晓凯.基于FPGA彩色图像自适应巴特沃斯滤波器及其应用[J]. 微电子学与计算机,2024,41(1):83-92. doi: 10.19304/J.ISSN1000-7180.2022.0627
引用本文: 韩玉鑫,王晓凯.基于FPGA彩色图像自适应巴特沃斯滤波器及其应用[J]. 微电子学与计算机,2024,41(1):83-92. doi: 10.19304/J.ISSN1000-7180.2022.0627
HAN Y X,WANG X K. FPGA-based adaptive Butterworth filter for color images and its applications[J]. Microelectronics & Computer,2024,41(1):83-92. doi: 10.19304/J.ISSN1000-7180.2022.0627
Citation: HAN Y X,WANG X K. FPGA-based adaptive Butterworth filter for color images and its applications[J]. Microelectronics & Computer,2024,41(1):83-92. doi: 10.19304/J.ISSN1000-7180.2022.0627

基于FPGA彩色图像自适应巴特沃斯滤波器及其应用

FPGA-based adaptive Butterworth filter for color images and its applications

  • 摘要: 传统巴特沃斯滤波器无法对不同图像自适应调整截止频率。针对此问题,提出频率自适应二维巴特沃斯滤波器,通过高频能量在图像总能量中所占比值,自适应地调整截止频率。所采用色彩空间为色相饱和度(Hue Saturation Intensity, HSI),数据格式由浮点数取代定点数,实现高速、高精度的2D-快速傅里叶变换(Fast Fourier Transform, FFT)和2D-快速傅里叶逆变换(Inverse Fast Fourier Transform, IFFT)。深度考虑Xilinx 7系列现场可编辑门阵列(Field Programmable Gate Array, FPGA) 硬件底层结构,在xc7a100tfgg484-3芯片上实现该滤波器,并在此基础上实现图像细节增强,增强后图像色彩无明显失真,图像细节更为丰富。经硬件仿真测试,分辨率为512×512的图像完成一次2D-FFT所需时间为6548.892 μs,与软件计算频谱结构相似度高达99.9998%。整个设计在资源、功耗和性能之间进行了权衡。

     

    Abstract: Traditional Butterworth filter cannot adaptively adjust the cutoff frequency for different images, in view of this problem, the proposed frequency adaptive two-dimensional Butterworth filter, through the high frequency band energy in the total image energy ratio, adaptively adjust the cutoff frequency. The color space used is Hue-Saturation-Intensity(HSI), and the data format replaces the fixed-point number with a floating-point number, achieving high-speed, high-precision 2D-Fast Fourier Transform(FFT) and 2D-Inverse Fast Fourier Transform(IFFT). Deeply considering the underlying structure of Xilinx 7 series Field Programmable Gate Array(FPGA) hardware, the filter is implemented on the xc7a100tfgg484-3 chip, and on this basis, the image details are enhanced, and the image color is colorless and the image details are richer. The hardware simulation results show that the image with a resolution of 512×512 takes 6548.892 μs to complete a 2D-FFT, which is 99.9998% similar to the spectrum structure calculated by software. The entire design trade-offs between resources, power consumption, and performance.

     

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