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XplorePlane/XP.ImageProcessing.Processors/边缘检测/KirschEdgeProcessor.cs
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2026-04-14 17:12:31 +08:00

133 lines
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C#

// ============================================================================
// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
// 文件名: KirschEdgeProcessor.cs
// 描述: Kirsch边缘检测算子,用于检测图像边缘
// 功能:
// - Kirsch算子边缘检测
// - 8个方向的边缘检测
// - 输出最大响应方向的边缘
// - 对噪声敏感度低
// 算法: Kirsch算子(8方向模板)
// 作者: 李伟 wei.lw.li@hexagon.com
// ============================================================================
using Emgu.CV;
using Emgu.CV.Structure;
using XP.ImageProcessing.Core;
using Serilog;
namespace XP.ImageProcessing.Processors;
/// <summary>
/// Kirsch边缘检测算子
/// </summary>
public class KirschEdgeProcessor : ImageProcessorBase
{
private static readonly ILogger _logger = Log.ForContext<KirschEdgeProcessor>();
// Kirsch算子的8个方向模板
private static readonly int[][,] KirschKernels = new int[8][,]
{
// N
new int[,] { { 5, 5, 5 }, { -3, 0, -3 }, { -3, -3, -3 } },
// NW
new int[,] { { 5, 5, -3 }, { 5, 0, -3 }, { -3, -3, -3 } },
// W
new int[,] { { 5, -3, -3 }, { 5, 0, -3 }, { 5, -3, -3 } },
// SW
new int[,] { { -3, -3, -3 }, { 5, 0, -3 }, { 5, 5, -3 } },
// S
new int[,] { { -3, -3, -3 }, { -3, 0, -3 }, { 5, 5, 5 } },
// SE
new int[,] { { -3, -3, -3 }, { -3, 0, 5 }, { -3, 5, 5 } },
// E
new int[,] { { -3, -3, 5 }, { -3, 0, 5 }, { -3, -3, 5 } },
// NE
new int[,] { { -3, 5, 5 }, { -3, 0, 5 }, { -3, -3, -3 } }
};
public KirschEdgeProcessor()
{
Name = LocalizationHelper.GetString("KirschEdgeProcessor_Name");
Description = LocalizationHelper.GetString("KirschEdgeProcessor_Description");
}
protected override void InitializeParameters()
{
Parameters.Add("Threshold", new ProcessorParameter(
"Threshold",
LocalizationHelper.GetString("KirschEdgeProcessor_Threshold"),
typeof(int),
100,
0,
1000,
LocalizationHelper.GetString("KirschEdgeProcessor_Threshold_Desc")));
Parameters.Add("Scale", new ProcessorParameter(
"Scale",
LocalizationHelper.GetString("KirschEdgeProcessor_Scale"),
typeof(double),
1.0,
0.1,
5.0,
LocalizationHelper.GetString("KirschEdgeProcessor_Scale_Desc")));
_logger.Debug("InitializeParameters");
}
public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
{
int threshold = GetParameter<int>("Threshold");
double scale = GetParameter<double>("Scale");
int width = inputImage.Width;
int height = inputImage.Height;
byte[,,] inputData = inputImage.Data;
Image<Gray, byte> result = new Image<Gray, byte>(width, height);
byte[,,] outputData = result.Data;
// 对每个像素应用8个Kirsch模板,取最大响应
for (int y = 1; y < height - 1; y++)
{
for (int x = 1; x < width - 1; x++)
{
int maxResponse = 0;
// 对8个方向分别计算
for (int k = 0; k < 8; k++)
{
int sum = 0;
for (int ky = 0; ky < 3; ky++)
{
for (int kx = 0; kx < 3; kx++)
{
int pixelValue = inputData[y + ky - 1, x + kx - 1, 0];
sum += pixelValue * KirschKernels[k][ky, kx];
}
}
// 取绝对值
sum = Math.Abs(sum);
if (sum > maxResponse)
{
maxResponse = sum;
}
}
// 应用阈值和缩放
if (maxResponse > threshold)
{
int value = (int)(maxResponse * scale);
outputData[y, x, 0] = (byte)Math.Min(255, Math.Max(0, value));
}
else
{
outputData[y, x, 0] = 0;
}
}
}
_logger.Debug("Process: Threshold = {Threshold}, Scale = {Scale}", threshold, scale);
return result;
}
}