canny边缘检测用verilog实现

Canny边缘检测算法在图像处理领域非常常用，它能够在图像中准确地检测出边缘，是数字图像处理中最流行的算法之一。下面是一个简单的Verilog实现，可以实现Canny算法的边缘检测。

首先，我们需要定义一些参数，如图像大小、高斯滤波器的大小、梯度阈值等。然后，我们需要对原始图像进行高斯滤波，以平滑图像并减少噪声。接下来，我们计算每个像素的梯度，以及每个像素的方向。然后，我们将梯度值与梯度阈值进行比较，并将具有较高梯度值的像素标记为边缘像素。最后，我们使用非极大值抑制算法，以滤除非极大值像素。

下面是一个简单的Canny边缘检测的Verilog实现：

module canny_edge_detection(input clk, input reset, input [7:0] image_in, output reg [7:0] edge_out);

// define image size and filter size
parameter WIDTH = 640;
parameter HEIGHT = 480;
parameter KERNEL_SIZE = 5;

// define threshold values
parameter LOW_THRESHOLD = 20;
parameter HIGH_THRESHOLD = 50;

reg [7:0] image_data [0:WIDTH-1][0:HEIGHT-1];
reg [7:0] smoothed_image [0:WIDTH-1][0:HEIGHT-1];
reg [7:0] gradient_map [0:WIDTH-1][0:HEIGHT-1];
reg [7:0] gradient_direction [0:WIDTH-1][0:HEIGHT-1];
reg [7:0] edge_map [0:WIDTH-1][0:HEIGHT-1];

// define Gaussian kernel
reg [7:0] kernel [0:KERNEL_SIZE-1];
initial begin
  kernel[0] = 1; kernel[KERNEL_SIZE-1] = 1;
  for (int i=1; i<KERNEL_SIZE-1; i=i+1) begin
    kernel[i] = 2;
  end
end

// apply Gaussian filter to input image
always @(posedge clk) begin
  if (reset) begin
    for (int i=0; i<WIDTH; i=i+1) begin
      for (int j=0; j<HEIGHT; j=j+1) begin
        image_data[i][j] = 0;
        smoothed_image[i][j] = 0;
        gradient_map[i][j] = 0;
        gradient_direction[i][j] = 0;
        edge_map[i][j] = 0;
      end
    end
  end
  else begin
    for (int i=0; i<WIDTH; i=i+1) begin
      for (int j=0; j<HEIGHT; j=j+1) begin
        image_data[i][j] = image_in;
        smoothed_image[i][j] = 0;
        gradient_map[i][j] = 0;
        gradient_direction[i][j] = 0;
        edge_map[i][j] = 0;
      end
    end
    for (int i=KERNEL_SIZE/2; i<WIDTH-KERNEL_SIZE/2; i=i+1) begin
      for (int j=KERNEL_SIZE/2; j<HEIGHT-KERNEL_SIZE/2; j=j+1) begin
        reg [15:0] sum = 0;
        for (int k=0; k<KERNEL_SIZE; k=k+1) begin
          for (int l=0; l<KERNEL_SIZE; l=l+1) begin
            sum = sum + image_data[i-k+KERNEL_SIZE/2][j-l+KERNEL_SIZE/2] * kernel[k] * kernel[l];
          end
        end
        smoothed_image[i][j] = sum >> (KERNEL_SIZE*2-1);
      end
    end
  end
end

// calculate gradient and direction
always @(posedge clk) begin
  if (reset) begin
    for (int i=0; i<WIDTH; i=i+1) begin
      for (int j=0; j<HEIGHT; j=j+1) begin
        gradient_map[i][j] = 0;
        gradient_direction[i][j] = 0;
      end
    end
  end
  else begin
    for (int i=1; i<WIDTH-1; i=i+1) begin
      for (int j=1; j<HEIGHT-1; j=j+1) begin
        reg [15:0] gx = smoothed_image[i+1][j-1] + 2*smoothed_image[i+1][j] + smoothed_image[i+1][j+1] - smoothed_image[i-1][j-1] - 2*smoothed_image[i-1][j] - smoothed_image[i-1][j+1];
        reg [15:0] gy = smoothed_image[i-1][j+1] + 2*smoothed_image[i][j+1] + smoothed_image[i+1][j+1] - smoothed_image[i-1][j-1] - 2*smoothed_image[i][j-1] - smoothed_image[i+1][j-1];
        gradient_map[i][j] = $sqrt(gx*gx + gy*gy);
        gradient_direction[i][j] = $atan2(gy, gx);
      end
    end
  end
end

// threshold gradient map and mark edge pixels
always @(posedge clk) begin
  if (reset) begin
    for (int i=0; i<WIDTH; i=i+1) begin
      for (int j=0; j<HEIGHT; j=j+1) begin
        edge_map[i][j] = 0;
      end
    end
  end
  else begin
    for (int i=1; i<WIDTH-1; i=i+1) begin
      for (int j=1; j<HEIGHT-1; j=j+1) begin
        if (gradient_map[i][j] > HIGH_THRESHOLD) begin
          edge_map[i][j] = 1;
        end
        else if (gradient_map[i][j] < LOW_THRESHOLD) begin
          edge_map[i][j] = 0;
        end
        else begin
          edge_map[i][j] = -1;
        end
      end
    end
    for (int i=1; i<WIDTH-1; i=i+1) begin
      for (int j=1; j<HEIGHT-1; j=j+1) begin
        if (edge_map[i][j] == 1) begin
          if ((gradient_direction[i][j] > -22.5 && gradient_direction[i][j] <= 22.5) || (gradient_direction[i][j] > 157.5 && gradient_direction[i][j] <= -157.5)) begin
            if (gradient_map[i][j] > gradient_map[i][j+1] && gradient_map[i][j] > gradient_map[i][j-1]) begin
              edge_map[i][j] = 1;
            end
            else begin
              edge_map[i][j] = 0;
            end
          end
          else if ((gradient_direction[i][j] > 22.5 && gradient_direction[i][j] <= 67.5) || (gradient_direction[i][j] > -157.5 && gradient_direction[i][j] <= -112.5)) begin
            if (gradient_map[i][j] > gradient_map[i+1][j+1] && gradient_map[i][j] > gradient_map[i-1][j-1]) begin
              edge_map[i][j] = 1;
            end
            else begin
              edge_map[i][j] = 0;
            end
          end
          else if ((gradient_direction[i][j] > 67.5 && gradient_direction[i][j] <= 112.5) || (gradient_direction[i][j] > -112.5 && gradient_direction[i][j] <= -67.5)) begin
            if (gradient_map[i][j] > gradient_map[i+1][j] && gradient_map[i][j] > gradient_map[i-1][j]) begin
              edge_map[i][j] = 1;
            end
            else begin
              edge_map[i][j] = 0;
            end
          end
          else if ((gradient_direction[i][j] > 112.5 && gradient_direction[i][j] <= 157.5) || (gradient_direction[i][j] > -67.5 && gradient_direction[i][j] <= -22.5)) begin
            if (gradient_map[i][j] > gradient_map[i+1][j-1] && gradient_map[i][j] > gradient_map[i-1][j+1]) begin
              edge_map[i][j] = 1;
            end
            else begin
              edge_map[i][j] = 0;
            end
          end
        end
      end
    end
  end
end

// output edge map
always @(posedge clk) begin
  if (reset) begin
    edge_out = 0;
  end
  else begin
    edge_out = edge_map[i][j];
  end
end

endmodule

注意，这只是一个简单的实现，可能需要进行优化以提高性能和准确性。此外，由于边缘检测算法本身的复杂性，可能需要使用更高级的工具来实现更复杂的算法。