2025年7月23日 星期三 2:48am

C# OpenCvSharp 图像滤波技巧

C#  OpenCvSharp 图像滤波技巧

目录

效果

平滑滤波

锐化滤波

高通滤波

中值滤波

双边滤波

自定义滤波

项目

代码

下载

效果

平滑滤波

平滑图像，减少噪点，让画面更加柔和。

锐化滤波

让细节更明显

高通滤波

高通滤波器，比如拉普拉斯滤波器，可以帮助我们识别边缘，让主体脱颖而出

中值滤波

对抗椒盐噪声

双边滤波

保持边缘的同时平滑

自定义滤波

项目

代码

using OpenCvSharp;
using System;
using System.Diagnostics;
using System.Drawing;
using System.Drawing.Imaging;
using System.Windows.Forms;

namespace OpenCvSharp_Demo
{
    public partial class Form1 : Form
    {
        public Form1()
        {
            InitializeComponent();
        }

        string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
        string startupPath;
        string image_path;

        Stopwatch stopwatch = new Stopwatch();

        Mat image;
        Mat result_image;

        private void Form1_Load(object sender, EventArgs e)
        {
            startupPath = System.Windows.Forms.Application.StartupPath;

            image_path = "1.jpg";
            pictureBox1.Image = new Bitmap(image_path);
            image = new Mat(image_path,ImreadModes.Grayscale);
        }

        private void button1_Click(object sender, EventArgs e)
        {
            OpenFileDialog ofd = new OpenFileDialog();
            ofd.Filter = fileFilter;
            if (ofd.ShowDialog() != DialogResult.OK) return;

            pictureBox1.Image = null;
            pictureBox2.Image = null;
            textBox1.Text = "";

            image_path = ofd.FileName;
            pictureBox1.Image = new Bitmap(image_path);
            image = new Mat(image_path);
        }

        ///


        /// 保存
        ///
        ///
        ///
        private void button3_Click(object sender, EventArgs e)
        {
            if (pictureBox2.Image == null)
            {
                return;
            }
            Bitmap output = new Bitmap(pictureBox2.Image);
            var sdf = new SaveFileDialog();
            sdf.Title = "保存图片";
            sdf.Filter = "Images (*.jpg)|*.jpg|Images (*.png)|*.png|Images (*.bmp)|*.bmp";
            if (sdf.ShowDialog() == DialogResult.OK)
            {
                switch (sdf.FilterIndex)
                {
                    case 1:
                        {
                            output.Save(sdf.FileName, ImageFormat.Jpeg);
                            break;
                        }
                    case 2:
                        {
                            output.Save(sdf.FileName, ImageFormat.Png);
                            break;
                        }
                    case 3:
                        {
                            output.Save(sdf.FileName, ImageFormat.Bmp);
                            break;
                        }
                }
                MessageBox.Show("保存成功，位置：" + sdf.FileName);
            }
        }

        ///


        /// 平滑滤波
        /// 平滑图像，减少噪点，让画面更加柔和。
        ///
        ///
        ///
        private void button2_Click(object sender, EventArgs e)
        {
            if (image_path == "")
            {
                return;
            }

            stopwatch.Restart();

            result_image = image.Clone();
            

            //平均模糊
            //Cv2.Blur(result_image, result_image, new OpenCvSharp.Size(5, 5));//(5, 5)是核大小，越大越模糊

            //高斯模糊
            Cv2.GaussianBlur(result_image, result_image, new OpenCvSharp.Size(5, 5), 0);//0表示自动选择sigma值


            double costTime = stopwatch.Elapsed.TotalMilliseconds;
            textBox1.Text = $"耗时:{costTime:F2}ms";
            pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());

        }

        ///


        /// 锐化滤波
        /// 让细节更明显
        ///
        ///
        ///
        private void button4_Click(object sender, EventArgs e)
        {
            if (image_path == "")
            {
                return;
            }

            stopwatch.Restart();
            result_image = new Mat();

            //定义锐化卷积核
            InputArray kernel = InputArray.Create(new float[3, 3] {
            { -1, -1, -1 },
            { -1, 9, -1 },
            { -1, -1, -1 } });

            Cv2.Filter2D(image, result_image, image.Type(), kernel);


            double costTime = stopwatch.Elapsed.TotalMilliseconds;
            textBox1.Text = $"耗时:{costTime:F2}ms";
            pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
        }

        ///


        /// 高通滤波
        /// 高通滤波器，比如拉普拉斯滤波器，可以帮助我们识别边缘，让主体脱颖而出
        ///
        ///
        ///
        private void button5_Click(object sender, EventArgs e)
        {
            if (image_path == "")
            {
                return;
            }

            stopwatch.Restart();


            result_image = new Mat();
            Cv2.Laplacian(image, result_image, MatType.CV_64F);
            Cv2.ConvertScaleAbs(result_image, result_image);
            result_image.ConvertTo(result_image, MatType.CV_8U);


            double costTime = stopwatch.Elapsed.TotalMilliseconds;
            textBox1.Text = $"耗时:{costTime:F2}ms";
            pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
        }

        ///


        /// 中值滤波
        /// 对抗椒盐噪声
        ///
        ///
        ///
        private void button6_Click(object sender, EventArgs e)
        {
            if (image_path == "")
            {
                return;
            }

            stopwatch.Restart();


            result_image = new Mat();
            Cv2.MedianBlur(image, result_image, 5);


            double costTime = stopwatch.Elapsed.TotalMilliseconds;
            textBox1.Text = $"耗时:{costTime:F2}ms";
            pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());

        }

        ///


        /// 双边滤波
        /// 保持边缘的同时平滑
        ///
        ///
        ///
        private void button7_Click(object sender, EventArgs e)
        {
            if (image_path == "")
            {
                return;
            }

            stopwatch.Restart();

            result_image = new Mat();
            Cv2.BilateralFilter(image, result_image, 9,75,75);

            double costTime = stopwatch.Elapsed.TotalMilliseconds;
            textBox1.Text = $"耗时:{costTime:F2}ms";
            pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
        }

        ///


        /// 自定义滤波
        ///
        ///
        ///
        private void button8_Click(object sender, EventArgs e)
        {
            if (image_path == "")
            {
                return;
            }

            stopwatch.Restart();
            result_image = new Mat();

            //定义卷积核
            InputArray kernel = InputArray.Create(new float[3, 3] {
            { 0, -1,0},
            { -1, 5, -1 },
            { 0, -1, 0 } });

            Cv2.Filter2D(image, result_image, image.Type(), kernel);


            double costTime = stopwatch.Elapsed.TotalMilliseconds;
            textBox1.Text = $"耗时:{costTime:F2}ms";
            pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());

        }
    }
}

  1. using OpenCvSharp;
  2. using System;
  3. using System.Diagnostics;
  4. using System.Drawing;
  5. using System.Drawing.Imaging;
  6. using System.Windows.Forms;
  7.  
  8. namespace OpenCvSharp_Demo
  9. {
  10.     public partial class Form1 : Form
  11.     {
  12.         public Form1()
  13.         {
  14.             InitializeComponent();
  15.         }
  16.  
  17.         string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
  18.         string startupPath;
  19.         string image_path;
  20.  
  21.         Stopwatch stopwatch = new Stopwatch();
  22.  
  23.         Mat image;
  24.         Mat result_image;
  25.  
  26.         private void Form1_Load(object sender, EventArgs e)
  27.         {
  28.             startupPath = System.Windows.Forms.Application.StartupPath;
  29.  
  30.             image_path = "1.jpg";
  31.             pictureBox1.Image = new Bitmap(image_path);
  32.             image = new Mat(image_path,ImreadModes.Grayscale);
  33.         }
  34.  
  35.         private void button1_Click(object sender, EventArgs e)
  36.         {
  37.             OpenFileDialog ofd = new OpenFileDialog();
  38.             ofd.Filter = fileFilter;
  39.             if (ofd.ShowDialog() != DialogResult.OK) return;
  40.  
  41.             pictureBox1.Image = null;
  42.             pictureBox2.Image = null;
  43.             textBox1.Text = "";
  44.  
  45.             image_path = ofd.FileName;
  46.             pictureBox1.Image = new Bitmap(image_path);
  47.             image = new Mat(image_path);
  48.         }
  49.  
  50.         /// <summary>
  51.         /// 保存
  52.         /// </summary>
  53.         /// <param name="sender"></param>
  54.         /// <param name="e"></param>
  55.         private void button3_Click(object sender, EventArgs e)
  56.         {
  57.             if (pictureBox2.Image == null)
  58.             {
  59.                 return;
  60.             }
  61.             Bitmap output = new Bitmap(pictureBox2.Image);
  62.             var sdf = new SaveFileDialog();
  63.             sdf.Title = "保存图片";
  64.             sdf.Filter = "Images (*.jpg)|*.jpg|Images (*.png)|*.png|Images (*.bmp)|*.bmp";
  65.             if (sdf.ShowDialog() == DialogResult.OK)
  66.             {
  67.                 switch (sdf.FilterIndex)
  68.                 {
  69.                     case 1:
  70.                         {
  71.                             output.Save(sdf.FileName, ImageFormat.Jpeg);
  72.                             break;
  73.                         }
  74.                     case 2:
  75.                         {
  76.                             output.Save(sdf.FileName, ImageFormat.Png);
  77.                             break;
  78.                         }
  79.                     case 3:
  80.                         {
  81.                             output.Save(sdf.FileName, ImageFormat.Bmp);
  82.                             break;
  83.                         }
  84.                 }
  85.                 MessageBox.Show("保存成功，位置：" + sdf.FileName);
  86.             }
  87.         }
  88.  
  89.         /// <summary>
  90.         /// 平滑滤波
  91.         /// 平滑图像，减少噪点，让画面更加柔和。
  92.         /// </summary>
  93.         /// <param name="sender"></param>
  94.         /// <param name="e"></param>
  95.         private void button2_Click(object sender, EventArgs e)
  96.         {
  97.             if (image_path == "")
  98.             {
  99.                 return;
  100.             }
  101.  
  102.             stopwatch.Restart();
  103.  
  104.             result_image = image.Clone();
  105.             
  106.  
  107.             //平均模糊
  108.             //Cv2.Blur(result_image, result_image, new OpenCvSharp.Size(5, 5));//(5, 5)是核大小，越大越模糊
  109.  
  110.             //高斯模糊
  111.             Cv2.GaussianBlur(result_image, result_image, new OpenCvSharp.Size(5, 5), 0);//0表示自动选择sigma值
  112.  
  113.  
  114.             double costTime = stopwatch.Elapsed.TotalMilliseconds;
  115.             textBox1.Text = $"耗时:{costTime:F2}ms";
  116.             pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
  117.  
  118.         }
  119.  
  120.         /// <summary>
  121.         /// 锐化滤波
  122.         /// 让细节更明显
  123.         /// </summary>
  124.         /// <param name="sender"></param>
  125.         /// <param name="e"></param>
  126.         private void button4_Click(object sender, EventArgs e)
  127.         {
  128.             if (image_path == "")
  129.             {
  130.                 return;
  131.             }
  132.  
  133.             stopwatch.Restart();
  134.             result_image = new Mat();
  135.  
  136.             //定义锐化卷积核
  137.             InputArray kernel = InputArray.Create<float>(new float[3, 3] {
  138.             { -1, -1, -1 },
  139.             { -1, 9, -1 },
  140.             { -1, -1, -1 } });
  141.  
  142.             Cv2.Filter2D(image, result_image, image.Type(), kernel);
  143.  
  144.  
  145.             double costTime = stopwatch.Elapsed.TotalMilliseconds;
  146.             textBox1.Text = $"耗时:{costTime:F2}ms";
  147.             pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
  148.         }
  149.  
  150.         /// <summary>
  151.         /// 高通滤波
  152.         /// 高通滤波器，比如拉普拉斯滤波器，可以帮助我们识别边缘，让主体脱颖而出
  153.         /// </summary>
  154.         /// <param name="sender"></param>
  155.         /// <param name="e"></param>
  156.         private void button5_Click(object sender, EventArgs e)
  157.         {
  158.             if (image_path == "")
  159.             {
  160.                 return;
  161.             }
  162.  
  163.             stopwatch.Restart();
  164.  
  165.  
  166.             result_image = new Mat();
  167.             Cv2.Laplacian(image, result_image, MatType.CV_64F);
  168.             Cv2.ConvertScaleAbs(result_image, result_image);
  169.             result_image.ConvertTo(result_image, MatType.CV_8U);
  170.  
  171.  
  172.             double costTime = stopwatch.Elapsed.TotalMilliseconds;
  173.             textBox1.Text = $"耗时:{costTime:F2}ms";
  174.             pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
  175.         }
  176.  
  177.         /// <summary>
  178.         /// 中值滤波
  179.         /// 对抗椒盐噪声
  180.         /// </summary>
  181.         /// <param name="sender"></param>
  182.         /// <param name="e"></param>
  183.         private void button6_Click(object sender, EventArgs e)
  184.         {
  185.             if (image_path == "")
  186.             {
  187.                 return;
  188.             }
  189.  
  190.             stopwatch.Restart();
  191.  
  192.  
  193.             result_image = new Mat();
  194.             Cv2.MedianBlur(image, result_image, 5);
  195.  
  196.  
  197.             double costTime = stopwatch.Elapsed.TotalMilliseconds;
  198.             textBox1.Text = $"耗时:{costTime:F2}ms";
  199.             pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
  200.  
  201.         }
  202.  
  203.         /// <summary>
  204.         /// 双边滤波
  205.         /// 保持边缘的同时平滑
  206.         /// </summary>
  207.         /// <param name="sender"></param>
  208.         /// <param name="e"></param>
  209.         private void button7_Click(object sender, EventArgs e)
  210.         {
  211.             if (image_path == "")
  212.             {
  213.                 return;
  214.             }
  215.  
  216.             stopwatch.Restart();
  217.  
  218.             result_image = new Mat();
  219.             Cv2.BilateralFilter(image, result_image, 9,75,75);
  220.  
  221.             double costTime = stopwatch.Elapsed.TotalMilliseconds;
  222.             textBox1.Text = $"耗时:{costTime:F2}ms";
  223.             pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
  224.         }
  225.  
  226.         /// <summary>
  227.         /// 自定义滤波
  228.         /// </summary>
  229.         /// <param name="sender"></param>
  230.         /// <param name="e"></param>
  231.         private void button8_Click(object sender, EventArgs e)
  232.         {
  233.             if (image_path == "")
  234.             {
  235.                 return;
  236.             }
  237.  
  238.             stopwatch.Restart();
  239.             result_image = new Mat();
  240.  
  241.             //定义卷积核
  242.             InputArray kernel = InputArray.Create<float>(new float[3, 3] {
  243.             { 0, -1,0},
  244.             { -1, 5, -1 },
  245.             { 0, -1, 0 } });
  246.  
  247.             Cv2.Filter2D(image, result_image, image.Type(), kernel);
  248.  
  249.  
  250.             double costTime = stopwatch.Elapsed.TotalMilliseconds;
  251.             textBox1.Text = $"耗时:{costTime:F2}ms";
  252.             pictureBox2.Image = new Bitmap(result_image.ToMemoryStream());
  253.  
  254.         }
  255.     }
  256. }

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