wei.lw.li
d5d964d115
滤波类：GaussianBlur(Sigma)、Bilateral(SigmaSpace)、 BandPass(FilterType,Order)、ShockFilter(Dt) 边缘检测：Sobel(Direction,KernelSize,Scale)、 HorizontalEdge(Method,Sensitivity)、Kirsch(Scale)
121 lines
4.3 KiB
C#
121 lines
4.3 KiB
C#
// ============================================================================
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// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
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// 文件名: KirschEdgeProcessor.cs
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// 描述: Kirsch边缘检测算子，用于检测图像边缘
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// 功能:
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// - Kirsch算子边缘检测
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// - 8个方向的边缘检测
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// - 输出最大响应方向的边缘
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// - 对噪声敏感度低
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// 算法: Kirsch算子（8方向模板）
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// 作者: 李伟 wei.lw.li@hexagon.com
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// ============================================================================
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using Emgu.CV;
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using Emgu.CV.Structure;
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using XP.ImageProcessing.Core;
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using Serilog;
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namespace XP.ImageProcessing.Processors;
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/// <summary>
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/// Kirsch边缘检测算子（支持 8 位和 16 位灰度图像）
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/// </summary>
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public class KirschEdgeProcessor<TDepth> : ImageProcessorBase<TDepth>
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where TDepth : struct, IComparable
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{
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private static readonly ILogger _logger = Log.ForContext<KirschEdgeProcessor<TDepth>>();
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// Kirsch算子的8个方向模板
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private static readonly int[][,] KirschKernels = new int[8][,]
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{
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// N
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new int[,] { { 5, 5, 5 }, { -3, 0, -3 }, { -3, -3, -3 } },
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// NW
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new int[,] { { 5, 5, -3 }, { 5, 0, -3 }, { -3, -3, -3 } },
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// W
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new int[,] { { 5, -3, -3 }, { 5, 0, -3 }, { 5, -3, -3 } },
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// SW
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new int[,] { { -3, -3, -3 }, { 5, 0, -3 }, { 5, 5, -3 } },
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// S
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new int[,] { { -3, -3, -3 }, { -3, 0, -3 }, { 5, 5, 5 } },
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// SE
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new int[,] { { -3, -3, -3 }, { -3, 0, 5 }, { -3, 5, 5 } },
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// E
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new int[,] { { -3, -3, 5 }, { -3, 0, 5 }, { -3, -3, 5 } },
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// NE
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new int[,] { { -3, 5, 5 }, { -3, 0, 5 }, { -3, -3, -3 } }
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};
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public KirschEdgeProcessor()
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{
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Name = LocalizationHelper.GetString("KirschEdgeProcessor_Name");
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Description = LocalizationHelper.GetString("KirschEdgeProcessor_Description");
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}
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protected override void InitializeParameters()
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{
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Parameters.Add("Threshold", new ProcessorParameter(
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"Threshold",
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LocalizationHelper.GetString("KirschEdgeProcessor_Threshold"),
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typeof(int),
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100,
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0,
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1000,
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LocalizationHelper.GetString("KirschEdgeProcessor_Threshold_Desc")));
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Parameters.Add("Scale", new ProcessorParameter(
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"Scale",
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LocalizationHelper.GetString("KirschEdgeProcessor_Scale"),
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typeof(double),
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1.0,
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0.1,
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5.0,
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LocalizationHelper.GetString("KirschEdgeProcessor_Scale_Desc")) { IsAdvanced = true });
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_logger.Debug("InitializeParameters");
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}
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public override Image<Gray, TDepth> Process(Image<Gray, TDepth> inputImage)
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{
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int threshold = GetParameter<int>("Threshold");
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double scale = GetParameter<double>("Scale");
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// 16 位图时阈值也按比例放大
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if (typeof(TDepth) == typeof(ushort))
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threshold = PixelDepthHelper.ScaleThreshold<TDepth>(threshold);
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int width = inputImage.Width;
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int height = inputImage.Height;
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var result = new Image<Gray, TDepth>(width, height);
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for (int y = 1; y < height - 1; y++)
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{
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for (int x = 1; x < width - 1; x++)
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{
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int maxResponse = 0;
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for (int k = 0; k < 8; k++)
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{
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int sum = 0;
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for (int ky = 0; ky < 3; ky++)
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for (int kx = 0; kx < 3; kx++)
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{
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int pixelValue = PixelDepthHelper.ReadPixel(inputImage, y + ky - 1, x + kx - 1);
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sum += pixelValue * KirschKernels[k][ky, kx];
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}
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sum = Math.Abs(sum);
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if (sum > maxResponse) maxResponse = sum;
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}
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if (maxResponse > threshold)
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{
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int value = (int)(maxResponse * scale);
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PixelDepthHelper.WritePixel(result, y, x, value);
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}
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}
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}
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_logger.Debug("Process: Threshold = {Threshold}, Scale = {Scale}", threshold, scale);
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return result;
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}
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} |