Difference of Gaussian Filter

The Difference of Gaussian Filter example uses four hardware functions from the Vitis vision library. They are:

xf::cv::GaussianBlur
xf::cv::duplicateMat
xf::cv::subtract

The Difference of Gaussian Filter function can be implemented by applying Gaussian Filter on the original source image, and that Gaussian blurred image is duplicated as two images. The Gaussian blur function is applied to one of the duplicated images, whereas the other one is stored as it is. Later, perform the Subtraction function on, two times Gaussian applied image and one of the duplicated image.

The following example demonstrates the Difference of Gaussian Filter example.

    void gaussiandiference(ap_uint<PTR_WIDTH>* img_in, float sigma, ap_uint<PTR_WIDTH>* img_out, int rows, int cols) {

#pragma HLS INTERFACE m_axi      port=img_in        offset=slave  bundle=gmem0
#pragma HLS INTERFACE m_axi      port=img_out       offset=slave  bundle=gmem1
#pragma HLS INTERFACE s_axilite  port=sigma
    #pragma HLS INTERFACE s_axilite  port=rows
    #pragma HLS INTERFACE s_axilite  port=cols
#pragma HLS INTERFACE s_axilite  port=return

            xf::cv::Mat<TYPE, HEIGHT, WIDTH, NPC1> imgInput(rows, cols);
            xf::cv::Mat<TYPE, HEIGHT, WIDTH, NPC1> imgin1(rows, cols);
            xf::cv::Mat<TYPE, HEIGHT, WIDTH, NPC1> imgin2(rows, cols);
            xf::cv::Mat<TYPE, HEIGHT, WIDTH, NPC1, 15360> imgin3(rows, cols);
            xf::cv::Mat<TYPE, HEIGHT, WIDTH, NPC1> imgin4(rows, cols);
            xf::cv::Mat<TYPE, HEIGHT, WIDTH, NPC1> imgOutput(rows, cols);

    #pragma HLS DATAFLOW

            // Retrieve xf::cv::Mat objects from img_in data:
            xf::cv::Array2xfMat<PTR_WIDTH, TYPE, HEIGHT, WIDTH, NPC1>(img_in, imgInput);

            // Run xfOpenCV kernel:
            xf::cv::GaussianBlur<FILTER_WIDTH, XF_BORDER_CONSTANT, TYPE, HEIGHT, WIDTH, NPC1>(imgInput, imgin1, sigma);
            xf::cv::duplicateMat<TYPE, HEIGHT, WIDTH, NPC1, 15360>(imgin1, imgin2, imgin3);
            xf::cv::GaussianBlur<FILTER_WIDTH, XF_BORDER_CONSTANT, TYPE, HEIGHT, WIDTH, NPC1>(imgin2, imgin4, sigma);
            xf::cv::subtract<XF_CONVERT_POLICY_SATURATE, TYPE, HEIGHT, WIDTH, NPC1, 15360>(imgin3, imgin4, imgOutput);

            // Convert output xf::cv::Mat object to output array:
            xf::cv::xfMat2Array<PTR_WIDTH, TYPE, HEIGHT, WIDTH, NPC1>(imgOutput, img_out);

            return;
    } // End of kernel

In the given example, the Gaussain Blur function is applied for source image imginput, and resultant image imgin1 is passed to xf::cv::duplicateMat. The imgin2 and imgin3 are the duplicate images of Gaussian applied image. Again gaussian blur is applied to imgin2 and the result is stored in imgin4. Now, perform the subtraction between imgin4 and imgin3, but here imgin3 has to wait up to at least one pixel of imgin4 generation. Finally the subtraction performed on imgin3 and imgin4.

Difference of Gaussian Filter - 2023.2 English

Vitis Libraries