Custom Convolution - 2023.2 English

The filter2D function performs convolution over an image using a user-defined kernel.

Convolution is a mathematical operation on two functions f and g, producing a third function, The third function is typically viewed as a modified version of one of the original functions, that gives the area overlap between the two functions to an extent that one of the original functions is translated.

The filter can be unity gain filter or a non-unity gain filter. The filter must be of type XF_16SP. If the co-efficients are floating point, it must be converted into the Qm.n and provided as the input as well as the shift parameter has to be set with the ‘n’ value. Else, if the input is not of floating point, the filter is provided directly and the shift parameter is set to zero.

API Syntax

template<int BORDER_TYPE,int FILTER_WIDTH,int FILTER_HEIGHT, int SRC_T,int DST_T, int ROWS, int COLS,int NPC=1, int XFCVDEPTH_IN_1 = _XFCVDEPTH_DEFAULT, int XFCVDEPTH_OUT_1 = _XFCVDEPTH_DEFAULT>
void filter2D(xf::cv::Mat<SRC_T, ROWS, COLS, NPC, XFCVDEPTH_IN_1> & _src_mat,xf::cv::Mat<DST_T, ROWS, COLS, NPC, XFCVDEPTH_OUT_1> & _dst_mat,short int filter[FILTER_HEIGHT*FILTER_WIDTH],unsigned char _shift)

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 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.

Performance Estimate

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