合并图像处理库，删除图像lib库

ImageProcessing.Processors/滤波处理/BandPassFilterProcessor.cs

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+// ============================================================================
+// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
+// 文件名: BandPassFilterProcessor.cs
+// 描述: 带通滤波器算子，用于频域图像处理
+// 功能:
+//   - 在频域中保留特定频率范围的信号
+//   - 支持理想、巴特沃斯、高斯三种滤波器类型
+//   - 可调节低频和高频截止频率
+//   - 通过FFT实现频域滤波
+// 算法: 基于离散傅里叶变换（DFT）的频域滤波
+// 作者: 李伟 wei.lw.li@hexagon.com
+// ============================================================================
+
+using Emgu.CV;
+using Emgu.CV.CvEnum;
+using Emgu.CV.Structure;
+using ImageProcessing.Core;
+using Serilog;
+using System.Drawing;
+
+namespace ImageProcessing.Processors;
+
+/// <summary>
+/// 带通滤波器算子
+/// </summary>
+public class BandPassFilterProcessor : ImageProcessorBase
+{
+    private static readonly ILogger _logger = Log.ForContext<BandPassFilterProcessor>();
+
+    public BandPassFilterProcessor()
+    {
+        Name = LocalizationHelper.GetString("BandPassFilterProcessor_Name");
+        Description = LocalizationHelper.GetString("BandPassFilterProcessor_Description");
+    }
+
+    protected override void InitializeParameters()
+    {
+        Parameters.Add("LowCutoff", new ProcessorParameter(
+            "LowCutoff",
+            LocalizationHelper.GetString("BandPassFilterProcessor_LowCutoff"),
+            typeof(int),
+            10,
+            1,
+            200,
+            LocalizationHelper.GetString("BandPassFilterProcessor_LowCutoff_Desc")));
+
+        Parameters.Add("HighCutoff", new ProcessorParameter(
+            "HighCutoff",
+            LocalizationHelper.GetString("BandPassFilterProcessor_HighCutoff"),
+            typeof(int),
+            50,
+            2,
+            500,
+            LocalizationHelper.GetString("BandPassFilterProcessor_HighCutoff_Desc")));
+
+        Parameters.Add("FilterType", new ProcessorParameter(
+            "FilterType",
+            LocalizationHelper.GetString("BandPassFilterProcessor_FilterType"),
+            typeof(string),
+            "Ideal",
+            null,
+            null,
+            LocalizationHelper.GetString("BandPassFilterProcessor_FilterType_Desc"),
+            new string[] { "Ideal", "Butterworth", "Gaussian" }));
+
+        Parameters.Add("Order", new ProcessorParameter(
+            "Order",
+            LocalizationHelper.GetString("BandPassFilterProcessor_Order"),
+            typeof(int),
+            2,
+            1,
+            10,
+            LocalizationHelper.GetString("BandPassFilterProcessor_Order_Desc")));
+        _logger.Debug("InitializeParameters");
+    }
+
+    public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
+    {
+        int lowCutoff = GetParameter<int>("LowCutoff");
+        int highCutoff = GetParameter<int>("HighCutoff");
+        string filterType = GetParameter<string>("FilterType");
+        int order = GetParameter<int>("Order");
+
+        if (highCutoff <= lowCutoff)
+        {
+            highCutoff = lowCutoff + 10;
+        }
+
+        var floatImage = inputImage.Convert<Gray, float>();
+        var imaginaryImage = new Image<Gray, float>(floatImage.Size);
+        imaginaryImage.SetZero();
+
+        using (var planes = new Emgu.CV.Util.VectorOfMat())
+        {
+            planes.Push(floatImage.Mat);
+            planes.Push(imaginaryImage.Mat);
+
+            Mat complexMat = new Mat();
+            CvInvoke.Merge(planes, complexMat);
+
+            Mat dftMat = new Mat();
+            CvInvoke.Dft(complexMat, dftMat, DxtType.Forward, 0);
+
+            var mask = CreateBandPassMask(floatImage.Size, lowCutoff, highCutoff, filterType, order);
+
+            using (var dftPlanes = new Emgu.CV.Util.VectorOfMat())
+            {
+                CvInvoke.Split(dftMat, dftPlanes);
+
+                Mat real = dftPlanes[0];
+                Mat imag = dftPlanes[1];
+
+                CvInvoke.Multiply(real, mask.Mat, real);
+                CvInvoke.Multiply(imag, mask.Mat, imag);
+
+                using (var filteredPlanes = new Emgu.CV.Util.VectorOfMat())
+                {
+                    filteredPlanes.Push(real);
+                    filteredPlanes.Push(imag);
+
+                    Mat filteredDft = new Mat();
+                    CvInvoke.Merge(filteredPlanes, filteredDft);
+
+                    Mat idftMat = new Mat();
+                    CvInvoke.Dft(filteredDft, idftMat, DxtType.Inverse | DxtType.Scale, 0);
+
+                    using (var idftPlanes = new Emgu.CV.Util.VectorOfMat())
+                    {
+                        CvInvoke.Split(idftMat, idftPlanes);
+
+                        var result = new Image<Gray, float>(floatImage.Size);
+                        idftPlanes[0].CopyTo(result);
+
+                        double minVal = 0, maxVal = 0;
+                        Point minLoc = new Point();
+                        Point maxLoc = new Point();
+                        CvInvoke.MinMaxLoc(result, ref minVal, ref maxVal, ref minLoc, ref maxLoc);
+
+                        if (maxVal > minVal)
+                        {
+                            result = (result - minVal) * (255.0 / (maxVal - minVal));
+                        }
+
+                        complexMat.Dispose();
+                        dftMat.Dispose();
+                        filteredDft.Dispose();
+                        idftMat.Dispose();
+                        _logger.Debug("Process: LowCutoff = {0}, HighCutoff = {1}, FilterType = {2}, Order = {3}", lowCutoff, highCutoff, filterType, order);
+                        return result.Convert<Gray, byte>();
+                    }
+                }
+            }
+        }
+    }
+
+    private Image<Gray, float> CreateBandPassMask(Size size, int lowCutoff, int highCutoff, string filterType, int order)
+    {
+        var mask = new Image<Gray, float>(size);
+        int cx = size.Width / 2;
+        int cy = size.Height / 2;
+
+        for (int y = 0; y < size.Height; y++)
+        {
+            for (int x = 0; x < size.Width; x++)
+            {
+                double dx = x - cx;
+                double dy = y - cy;
+                double distance = Math.Sqrt(dx * dx + dy * dy);
+
+                float value = 0;
+
+                switch (filterType)
+                {
+                    case "理想":
+                        value = (distance >= lowCutoff && distance <= highCutoff) ? 1.0f : 0.0f;
+                        break;
+
+                    case "巴特沃斯":
+                        double highPass = 1.0 / (1.0 + Math.Pow(lowCutoff / (distance + 0.001), 2 * order));
+                        double lowPass = 1.0 / (1.0 + Math.Pow(distance / (highCutoff + 0.001), 2 * order));
+                        value = (float)(highPass * lowPass);
+                        break;
+
+                    case "高斯":
+                        double highPassGaussian = 1.0 - Math.Exp(-distance * distance / (2.0 * lowCutoff * lowCutoff));
+                        double lowPassGaussian = Math.Exp(-distance * distance / (2.0 * highCutoff * highCutoff));
+                        value = (float)(highPassGaussian * lowPassGaussian);
+                        break;
+                }
+
+                mask.Data[y, x, 0] = value;
+            }
+        }
+
+        return mask;
+    }
+}

ImageProcessing.Processors/滤波处理/BilateralFilterProcessor.cs

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+// ============================================================================
+// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
+// 文件名: BilateralFilterProcessor.cs
+// 描述: 双边滤波算子，用于保边降噪
+// 功能:
+//   - 双边滤波
+//   - 保持边缘清晰的同时平滑图像
+//   - 可调节核大小和标准差
+// 算法: 双边滤波
+// 作者: 李伟 wei.lw.li@hexagon.com
+// ============================================================================
+
+using Emgu.CV;
+using Emgu.CV.Structure;
+using ImageProcessing.Core;
+using Serilog;
+
+namespace ImageProcessing.Processors;
+
+/// <summary>
+/// 双边滤波算子
+/// </summary>
+public class BilateralFilterProcessor : ImageProcessorBase
+{
+    private static readonly ILogger _logger = Log.ForContext<BilateralFilterProcessor>();
+
+    public BilateralFilterProcessor()
+    {
+        Name = LocalizationHelper.GetString("BilateralFilterProcessor_Name");
+        Description = LocalizationHelper.GetString("BilateralFilterProcessor_Description");
+    }
+
+    protected override void InitializeParameters()
+    {
+        Parameters.Add("Diameter", new ProcessorParameter(
+            "Diameter",
+            LocalizationHelper.GetString("BilateralFilterProcessor_Diameter"),
+            typeof(int),
+            9,
+            1,
+            31,
+            LocalizationHelper.GetString("BilateralFilterProcessor_Diameter_Desc")));
+
+        Parameters.Add("SigmaColor", new ProcessorParameter(
+            "SigmaColor",
+            LocalizationHelper.GetString("BilateralFilterProcessor_SigmaColor"),
+            typeof(double),
+            75.0,
+            1.0,
+            200.0,
+            LocalizationHelper.GetString("BilateralFilterProcessor_SigmaColor_Desc")));
+
+        Parameters.Add("SigmaSpace", new ProcessorParameter(
+            "SigmaSpace",
+            LocalizationHelper.GetString("BilateralFilterProcessor_SigmaSpace"),
+            typeof(double),
+            75.0,
+            1.0,
+            200.0,
+            LocalizationHelper.GetString("BilateralFilterProcessor_SigmaSpace_Desc")));
+
+        _logger.Debug("InitializeParameters");
+    }
+
+    public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
+    {
+        int diameter = GetParameter<int>("Diameter");
+        double sigmaColor = GetParameter<double>("SigmaColor");
+        double sigmaSpace = GetParameter<double>("SigmaSpace");
+
+        var result = inputImage.Clone();
+        CvInvoke.BilateralFilter(inputImage, result, diameter, sigmaColor, sigmaSpace);
+
+        _logger.Debug("Process: Diameter = {Diameter}, SigmaColor = {SigmaColor}, SigmaSpace = {SigmaSpace}",
+            diameter, sigmaColor, sigmaSpace);
+        return result;
+    }
+}

ImageProcessing.Processors/滤波处理/GaussianBlurProcessor.cs

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+// ============================================================================
+// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
+// 文件名: GaussianBlurProcessor.cs
+// 描述: 高斯模糊算子，用于图像平滑和降噪
+// 功能:
+//   - 高斯核卷积平滑
+//   - 可调节核大小和标准差
+//   - 有效去除高斯噪声
+//   - 保持边缘相对清晰
+// 算法: 高斯滤波器卷积
+// 作者: 李伟 wei.lw.li@hexagon.com
+// ============================================================================
+
+using Emgu.CV;
+using Emgu.CV.Structure;
+using ImageProcessing.Core;
+using Serilog;
+
+namespace ImageProcessing.Processors;
+
+/// <summary>
+/// 高斯模糊算子
+/// </summary>
+public class GaussianBlurProcessor : ImageProcessorBase
+{
+    private static readonly ILogger _logger = Log.ForContext<GammaProcessor>();
+
+    public GaussianBlurProcessor()
+    {
+        Name = LocalizationHelper.GetString("GaussianBlurProcessor_Name");
+        Description = LocalizationHelper.GetString("GaussianBlurProcessor_Description");
+    }
+
+    protected override void InitializeParameters()
+    {
+        Parameters.Add("KernelSize", new ProcessorParameter(
+            "KernelSize",
+            LocalizationHelper.GetString("GaussianBlurProcessor_KernelSize"),
+            typeof(int),
+            5,
+            1,
+            31,
+            LocalizationHelper.GetString("GaussianBlurProcessor_KernelSize_Desc")));
+
+        Parameters.Add("Sigma", new ProcessorParameter(
+            "Sigma",
+            LocalizationHelper.GetString("GaussianBlurProcessor_Sigma"),
+            typeof(double),
+            1.5,
+            0.1,
+            10.0,
+            LocalizationHelper.GetString("GaussianBlurProcessor_Sigma_Desc")));
+        _logger.Debug("InitializeParameters");
+    }
+
+    public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
+    {
+        int kernelSize = GetParameter<int>("KernelSize");
+        double sigma = GetParameter<double>("Sigma");
+
+        if (kernelSize % 2 == 0) kernelSize++;
+
+        var result = inputImage.Clone();
+        CvInvoke.GaussianBlur(inputImage, result,
+            new System.Drawing.Size(kernelSize, kernelSize), sigma);
+        _logger.Debug("Process: KernelSize = {KernelSize}, Sigma = {Sigma}", kernelSize, sigma);
+        return result;
+    }
+}

ImageProcessing.Processors/滤波处理/HighPassFilterProcessor.cs

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+// ============================================================================
+// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
+// 文件名: HighPassFilterProcessor.cs
+// 描述: 高通滤波算子，用于边缘增强
+// 功能:
+//   - 高通滤波（频域）
+//   - 边缘增强
+//   - 去除低频信息
+//   - 可调节截止频率
+// 算法: 高斯高通滤波器（频域）
+// 作者: 李伟 wei.lw.li@hexagon.com
+// ============================================================================
+
+using Emgu.CV;
+using Emgu.CV.CvEnum;
+using Emgu.CV.Structure;
+using ImageProcessing.Core;
+using Serilog;
+
+namespace ImageProcessing.Processors;
+
+/// <summary>
+/// 高通滤波算子
+/// </summary>
+public class HighPassFilterProcessor : ImageProcessorBase
+{
+    private static readonly ILogger _logger = Log.ForContext<HighPassFilterProcessor>();
+
+    public HighPassFilterProcessor()
+    {
+        Name = LocalizationHelper.GetString("HighPassFilterProcessor_Name");
+        Description = LocalizationHelper.GetString("HighPassFilterProcessor_Description");
+    }
+
+    protected override void InitializeParameters()
+    {
+        Parameters.Add("CutoffFrequency", new ProcessorParameter(
+            "CutoffFrequency",
+            LocalizationHelper.GetString("HighPassFilterProcessor_CutoffFrequency"),
+            typeof(double),
+            30.0,
+            1.0,
+            200.0,
+            LocalizationHelper.GetString("HighPassFilterProcessor_CutoffFrequency_Desc")));
+
+        _logger.Debug("InitializeParameters");
+    }
+
+    public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
+    {
+        double cutoffFrequency = GetParameter<double>("CutoffFrequency");
+
+        int rows = inputImage.Rows;
+        int cols = inputImage.Cols;
+
+        // 转换为浮点型
+        Image<Gray, float> floatImage = inputImage.Convert<Gray, float>();
+
+        // 创建复数图像用于FFT
+        Mat complexImage = new Mat();
+        using (var planes = new Emgu.CV.Util.VectorOfMat())
+        {
+            planes.Push(floatImage.Mat);
+            planes.Push(Mat.Zeros(rows, cols, DepthType.Cv32F, 1));
+            CvInvoke.Merge(planes, complexImage);
+        }
+
+        // 执行DFT
+        Mat dftImage = new Mat();
+        CvInvoke.Dft(complexImage, dftImage, DxtType.Forward);
+
+        // 分离实部和虚部
+        using (var dftPlanes = new Emgu.CV.Util.VectorOfMat())
+        {
+            CvInvoke.Split(dftImage, dftPlanes);
+
+            Mat real = dftPlanes[0];
+            Mat imag = dftPlanes[1];
+
+            // 创建高通滤波器
+            Mat filter = CreateHighPassFilter(rows, cols, cutoffFrequency);
+
+            // 应用滤波器
+            CvInvoke.Multiply(real, filter, real);
+            CvInvoke.Multiply(imag, filter, imag);
+
+            // 合并并执行逆DFT
+            using (var filteredPlanes = new Emgu.CV.Util.VectorOfMat())
+            {
+                filteredPlanes.Push(real);
+                filteredPlanes.Push(imag);
+
+                Mat filteredDft = new Mat();
+                CvInvoke.Merge(filteredPlanes, filteredDft);
+
+                Mat ifftImage = new Mat();
+                CvInvoke.Dft(filteredDft, ifftImage, DxtType.Inverse | DxtType.Scale);
+
+                // 分离实部
+                using (var ifftPlanes = new Emgu.CV.Util.VectorOfMat())
+                {
+                    CvInvoke.Split(ifftImage, ifftPlanes);
+
+                    // 转换回byte类型
+                    Mat resultMat = new Mat();
+                    ifftPlanes[0].ConvertTo(resultMat, DepthType.Cv8U);
+
+                    Image<Gray, byte> result = resultMat.ToImage<Gray, byte>();
+
+                    // 释放资源
+                    floatImage.Dispose();
+                    complexImage.Dispose();
+                    dftImage.Dispose();
+                    filter.Dispose();
+                    filteredDft.Dispose();
+                    ifftImage.Dispose();
+                    resultMat.Dispose();
+
+                    _logger.Debug("Process: CutoffFrequency = {CutoffFrequency}", cutoffFrequency);
+                    return result;
+                }
+            }
+        }
+    }
+
+    /// <summary>
+    /// 创建高斯高通滤波器
+    /// </summary>
+    private Mat CreateHighPassFilter(int rows, int cols, double d0)
+    {
+        var filter = new Image<Gray, float>(cols, rows);
+
+        int centerX = cols / 2;
+        int centerY = rows / 2;
+
+        for (int i = 0; i < rows; i++)
+        {
+            for (int j = 0; j < cols; j++)
+            {
+                double distance = Math.Sqrt(Math.Pow(i - centerY, 2) + Math.Pow(j - centerX, 2));
+                float value = (float)(1 - Math.Exp(-(distance * distance) / (2 * d0 * d0)));
+                filter.Data[i, j, 0] = value;
+            }
+        }
+
+        return filter.Mat;
+    }
+}

ImageProcessing.Processors/滤波处理/LowPassFilterProcessor.cs

@@ -0,0 +1,148 @@
+// ============================================================================
+// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
+// 文件名: LowPassFilterProcessor.cs
+// 描述: 低通滤波算子，用于去除高频噪声
+// 功能:
+//   - 低通滤波（频域）
+//   - 去除高频噪声
+//   - 平滑图像
+//   - 可调节截止频率
+// 算法: 高斯低通滤波器（频域）
+// 作者: 李伟 wei.lw.li@hexagon.com
+// ============================================================================
+
+using Emgu.CV;
+using Emgu.CV.CvEnum;
+using Emgu.CV.Structure;
+using ImageProcessing.Core;
+using Serilog;
+
+namespace ImageProcessing.Processors;
+
+/// <summary>
+/// 低通滤波算子
+/// </summary>
+public class LowPassFilterProcessor : ImageProcessorBase
+{
+    private static readonly ILogger _logger = Log.ForContext<LowPassFilterProcessor>();
+
+    public LowPassFilterProcessor()
+    {
+        Name = LocalizationHelper.GetString("LowPassFilterProcessor_Name");
+        Description = LocalizationHelper.GetString("LowPassFilterProcessor_Description");
+    }
+
+    protected override void InitializeParameters()
+    {
+        Parameters.Add("CutoffFrequency", new ProcessorParameter(
+            "CutoffFrequency",
+            LocalizationHelper.GetString("LowPassFilterProcessor_CutoffFrequency"),
+            typeof(double),
+            30.0,
+            1.0,
+            200.0,
+            LocalizationHelper.GetString("LowPassFilterProcessor_CutoffFrequency_Desc")));
+
+        _logger.Debug("InitializeParameters");
+    }
+
+    public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
+    {
+        double cutoffFrequency = GetParameter<double>("CutoffFrequency");
+
+        int rows = inputImage.Rows;
+        int cols = inputImage.Cols;
+
+        // 转换为浮点型
+        Image<Gray, float> floatImage = inputImage.Convert<Gray, float>();
+
+        // 创建复数图像用于FFT
+        Mat complexImage = new Mat();
+        using (var planes = new Emgu.CV.Util.VectorOfMat())
+        {
+            planes.Push(floatImage.Mat);
+            planes.Push(Mat.Zeros(rows, cols, DepthType.Cv32F, 1));
+            CvInvoke.Merge(planes, complexImage);
+        }
+
+        // 执行DFT
+        Mat dftImage = new Mat();
+        CvInvoke.Dft(complexImage, dftImage, DxtType.Forward);
+
+        // 分离实部和虚部
+        using (var dftPlanes = new Emgu.CV.Util.VectorOfMat())
+        {
+            CvInvoke.Split(dftImage, dftPlanes);
+
+            Mat real = dftPlanes[0];
+            Mat imag = dftPlanes[1];
+
+            // 创建低通滤波器
+            Mat filter = CreateLowPassFilter(rows, cols, cutoffFrequency);
+
+            // 应用滤波器
+            CvInvoke.Multiply(real, filter, real);
+            CvInvoke.Multiply(imag, filter, imag);
+
+            // 合并并执行逆DFT
+            using (var filteredPlanes = new Emgu.CV.Util.VectorOfMat())
+            {
+                filteredPlanes.Push(real);
+                filteredPlanes.Push(imag);
+
+                Mat filteredDft = new Mat();
+                CvInvoke.Merge(filteredPlanes, filteredDft);
+
+                Mat ifftImage = new Mat();
+                CvInvoke.Dft(filteredDft, ifftImage, DxtType.Inverse | DxtType.Scale);
+
+                // 分离实部
+                using (var ifftPlanes = new Emgu.CV.Util.VectorOfMat())
+                {
+                    CvInvoke.Split(ifftImage, ifftPlanes);
+
+                    // 转换回byte类型
+                    Mat resultMat = new Mat();
+                    ifftPlanes[0].ConvertTo(resultMat, DepthType.Cv8U);
+
+                    Image<Gray, byte> result = resultMat.ToImage<Gray, byte>();
+
+                    // 释放资源
+                    floatImage.Dispose();
+                    complexImage.Dispose();
+                    dftImage.Dispose();
+                    filter.Dispose();
+                    filteredDft.Dispose();
+                    ifftImage.Dispose();
+                    resultMat.Dispose();
+
+                    _logger.Debug("Process: CutoffFrequency = {CutoffFrequency}", cutoffFrequency);
+                    return result;
+                }
+            }
+        }
+    }
+
+    /// <summary>
+    /// 创建高斯低通滤波器
+    /// </summary>
+    private Mat CreateLowPassFilter(int rows, int cols, double d0)
+    {
+        var filter = new Image<Gray, float>(cols, rows);
+
+        int centerX = cols / 2;
+        int centerY = rows / 2;
+
+        for (int i = 0; i < rows; i++)
+        {
+            for (int j = 0; j < cols; j++)
+            {
+                double distance = Math.Sqrt(Math.Pow(i - centerY, 2) + Math.Pow(j - centerX, 2));
+                float value = (float)Math.Exp(-(distance * distance) / (2 * d0 * d0));
+                filter.Data[i, j, 0] = value;
+            }
+        }
+
+        return filter.Mat;
+    }
+}

ImageProcessing.Processors/滤波处理/MeanFilterProcessor.cs

@@ -0,0 +1,61 @@
+// ============================================================================
+// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
+// 文件名: MeanFilterProcessor.cs
+// 描述: 均值滤波算子，用于图像平滑
+// 功能:
+//   - 均值滤波
+//   - 简单快速的平滑方法
+//   - 可调节核大小
+// 算法: 均值滤波
+// 作者: 李伟 wei.lw.li@hexagon.com
+// ============================================================================
+
+using Emgu.CV;
+using Emgu.CV.Structure;
+using ImageProcessing.Core;
+using Serilog;
+using System.Drawing;
+
+namespace ImageProcessing.Processors;
+
+/// <summary>
+/// 均值滤波算子
+/// </summary>
+public class MeanFilterProcessor : ImageProcessorBase
+{
+    private static readonly ILogger _logger = Log.ForContext<MeanFilterProcessor>();
+
+    public MeanFilterProcessor()
+    {
+        Name = LocalizationHelper.GetString("MeanFilterProcessor_Name");
+        Description = LocalizationHelper.GetString("MeanFilterProcessor_Description");
+    }
+
+    protected override void InitializeParameters()
+    {
+        Parameters.Add("KernelSize", new ProcessorParameter(
+            "KernelSize",
+            LocalizationHelper.GetString("MeanFilterProcessor_KernelSize"),
+            typeof(int),
+            5,
+            1,
+            31,
+            LocalizationHelper.GetString("MeanFilterProcessor_KernelSize_Desc")));
+
+        _logger.Debug("InitializeParameters");
+    }
+
+    public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
+    {
+        int kernelSize = GetParameter<int>("KernelSize");
+
+        // 确保核大小为奇数
+        if (kernelSize % 2 == 0) kernelSize++;
+
+        var result = inputImage.Clone();
+        CvInvoke.Blur(inputImage, result, new Size(kernelSize, kernelSize), new Point(-1, -1));
+
+        _logger.Debug("Process: KernelSize = {KernelSize}", kernelSize);
+        return result;
+    }
+}

ImageProcessing.Processors/滤波处理/MedianFilterProcessor.cs

@@ -0,0 +1,61 @@
+// ============================================================================
+// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
+// 文件名: MedianFilterProcessor.cs
+// 描述: 中值滤波算子，用于去除椒盐噪声
+// 功能:
+//   - 中值滤波
+//   - 有效去除椒盐噪声
+//   - 保持边缘清晰
+//   - 可调节核大小
+// 算法: 中值滤波
+// 作者: 李伟 wei.lw.li@hexagon.com
+// ============================================================================
+
+using Emgu.CV;
+using Emgu.CV.Structure;
+using ImageProcessing.Core;
+using Serilog;
+
+namespace ImageProcessing.Processors;
+
+/// <summary>
+/// 中值滤波算子
+/// </summary>
+public class MedianFilterProcessor : ImageProcessorBase
+{
+    private static readonly ILogger _logger = Log.ForContext<MedianFilterProcessor>();
+
+    public MedianFilterProcessor()
+    {
+        Name = LocalizationHelper.GetString("MedianFilterProcessor_Name");
+        Description = LocalizationHelper.GetString("MedianFilterProcessor_Description");
+    }
+
+    protected override void InitializeParameters()
+    {
+        Parameters.Add("KernelSize", new ProcessorParameter(
+            "KernelSize",
+            LocalizationHelper.GetString("MedianFilterProcessor_KernelSize"),
+            typeof(int),
+            5,
+            1,
+            31,
+            LocalizationHelper.GetString("MedianFilterProcessor_KernelSize_Desc")));
+
+        _logger.Debug("InitializeParameters");
+    }
+
+    public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
+    {
+        int kernelSize = GetParameter<int>("KernelSize");
+
+        // 确保核大小为奇数
+        if (kernelSize % 2 == 0) kernelSize++;
+
+        var result = inputImage.Clone();
+        CvInvoke.MedianBlur(inputImage, result, kernelSize);
+
+        _logger.Debug("Process: KernelSize = {KernelSize}", kernelSize);
+        return result;
+    }
+}

ImageProcessing.Processors/滤波处理/ShockFilterProcessor.cs

@@ -0,0 +1,123 @@
+// ============================================================================
+// Copyright © 2026 Hexagon Technology Center GmbH. All Rights Reserved.
+// 文件名: ShockFilterProcessor.cs
+// 描述: 冲击滤波算子，用于图像锐化和边缘增强
+// 功能:
+//   - 基于PDE的图像锐化
+//   - 增强边缘同时保持平滑区域
+//   - 可调节迭代次数和滤波强度
+//   - 适用于模糊图像的恢复
+// 算法: 冲击滤波器（Shock Filter）基于偏微分方程
+// 作者: 李伟 wei.lw.li@hexagon.com
+// ============================================================================
+
+using Emgu.CV;
+using Emgu.CV.Structure;
+using ImageProcessing.Core;
+using Serilog;
+
+namespace ImageProcessing.Processors;
+
+/// <summary>
+/// 冲击滤波算子
+/// </summary>
+public class ShockFilterProcessor : ImageProcessorBase
+{
+    private static readonly ILogger _logger = Log.ForContext<ShockFilterProcessor>();
+
+    public ShockFilterProcessor()
+    {
+        Name = LocalizationHelper.GetString("ShockFilterProcessor_Name");
+        Description = LocalizationHelper.GetString("ShockFilterProcessor_Description");
+    }
+
+    protected override void InitializeParameters()
+    {
+        Parameters.Add("Iterations", new ProcessorParameter(
+            "Iterations",
+            LocalizationHelper.GetString("ShockFilterProcessor_Iterations"),
+            typeof(int),
+            5,
+            1,
+            20,
+            LocalizationHelper.GetString("ShockFilterProcessor_Iterations_Desc")));
+
+        Parameters.Add("Theta", new ProcessorParameter(
+            "Theta",
+            LocalizationHelper.GetString("ShockFilterProcessor_Theta"),
+            typeof(double),
+            0.5,
+            0.0,
+            2.0,
+            LocalizationHelper.GetString("ShockFilterProcessor_Theta_Desc")));
+
+        Parameters.Add("Dt", new ProcessorParameter(
+            "Dt",
+            LocalizationHelper.GetString("ShockFilterProcessor_Dt"),
+            typeof(double),
+            0.25,
+            0.1,
+            1.0,
+            LocalizationHelper.GetString("ShockFilterProcessor_Dt_Desc")));
+        _logger.Debug("InitializeParameters");
+    }
+
+    public override Image<Gray, byte> Process(Image<Gray, byte> inputImage)
+    {
+        int iterations = GetParameter<int>("Iterations");
+        double theta = GetParameter<double>("Theta");
+        double dt = GetParameter<double>("Dt");
+        var result = inputImage.Convert<Gray, float>();
+        for (int iter = 0; iter < iterations; iter++)
+        {
+            result = ShockFilterIteration(result, theta, dt);
+        }
+        _logger.Debug("Process: Iterations = {Iterations}, Theta = {Theta}, Dt = {Dt}", iterations, theta, dt);
+        return result.Convert<Gray, byte>();
+    }
+
+    private Image<Gray, float> ShockFilterIteration(Image<Gray, float> input, double theta, double dt)
+    {
+        int width = input.Width;
+        int height = input.Height;
+        var output = new Image<Gray, float>(width, height);
+
+        for (int y = 1; y < height - 1; y++)
+        {
+            for (int x = 1; x < width - 1; x++)
+            {
+                float dx = (input.Data[y, x + 1, 0] - input.Data[y, x - 1, 0]) / 2.0f;
+                float dy = (input.Data[y + 1, x, 0] - input.Data[y - 1, x, 0]) / 2.0f;
+                float gradMag = (float)Math.Sqrt(dx * dx + dy * dy);
+
+                float dxx = input.Data[y, x + 1, 0] - 2 * input.Data[y, x, 0] + input.Data[y, x - 1, 0];
+                float dyy = input.Data[y + 1, x, 0] - 2 * input.Data[y, x, 0] + input.Data[y - 1, x, 0];
+                float laplacian = dxx + dyy;
+
+                float sign = laplacian > 0 ? 1.0f : -1.0f;
+
+                if (gradMag > theta)
+                {
+                    output.Data[y, x, 0] = input.Data[y, x, 0] - (float)(dt * sign * gradMag);
+                }
+                else
+                {
+                    output.Data[y, x, 0] = input.Data[y, x, 0];
+                }
+            }
+        }
+
+        for (int x = 0; x < width; x++)
+        {
+            output.Data[0, x, 0] = input.Data[0, x, 0];
+            output.Data[height - 1, x, 0] = input.Data[height - 1, x, 0];
+        }
+        for (int y = 0; y < height; y++)
+        {
+            output.Data[y, 0, 0] = input.Data[y, 0, 0];
+            output.Data[y, width - 1, 0] = input.Data[y, width - 1, 0];
+        }
+
+        return output;
+    }
+}