Sobel Filter - 2023.2 English

The Sobel function Computes the gradients of input image in both x and y direction by convolving the kernel with input image being processed.

• For Kernel size 3x3
  • GradientX:
  • GradientY:
• For Kernel size 5x5
  • GradientX:
  • GradientY:
• For Kernel size 7x7
  • GradientX:
  • GradientY:

API Syntax

template<int BORDER_TYPE,int FILTER_TYPE, int SRC_T,int DST_T, int ROWS, int COLS,int NPC=1, bool USE_URAM=false, int XFCVDEPTH_IN = _XFCVDEPTH_DEFAULT, int XFCVDEPTH_OUT_X = _XFCVDEPTH_DEFAULT, int XFCVDEPTH_OUT_Y = _XFCVDEPTH_DEFAULT>
void Sobel(xf::cv::Mat<SRC_T, ROWS, COLS, NPC, XFCVDEPTH_IN> & _src_mat,xf::cv::Mat<DST_T, ROWS, COLS, NPC, XFCVDEPTH_OUT_X> & _dst_matx,xf::cv::Mat<DST_T, ROWS, COLS, NPC, XFCVDEPTH_OUT_Y> & _dst_maty)

Parameter Descriptions

The following table describes the template and the function parameters.

Resource Utilization

The following table summarizes the resource utilization of the kernel in different configurations, generated using Vivado HLS 2019.1 tool for the Xilinx Xczu9eg-ffvb1156-1-i-es1 FPGA, to process a grayscale HD (1080x1920) image.

The following table summarizes the resource utilization of the kernel in different configurations, generated using Vivado HLS 2019.1 tool for the Xilinx Xczu9eg-ffvb1156-1-i-es1 FPGA, to process a 4K 3 Channel image.

The following table summarizes the resource utilization of the kernel in different configurations, generated using Vivado HLS 2019.1 tool for the Xilinx xczu7ev-ffvc1156-2-e FPGA, to process a grayscale 4K (3840x2160) image with UltraRAM enable.

Performance Estimate

The following table summarizes the performance of the kernel in different configurations, as generated using Vivado HLS 2019.1 tool for the Xilinx Xczu9eg-ffvb1156-1-i-es1, to process a grayscale HD (1080x1920) image.