效果

直方图

直方图均衡化

自适应的直方图均衡化

全局直方图均衡化

局部直方图均衡化

对比度调整

项目

代码

using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Windows.Forms;
using OpenCvSharp;
namespace OpenCvSharp_图像去雾
{
 public partial class Form1 : Form
 {
 public Form1()
 {
 InitializeComponent();
 }
 string fileFilter = "*.*|*.bmp;*.jpg;*.jpeg;*.tiff;*.tiff;*.png";
 string imgPath = "";
 private void button1_Click(object sender, EventArgs e)
 {
 OpenFileDialog ofd = new OpenFileDialog();
 ofd.Filter = fileFilter;
if (ofd.ShowDialog() != DialogResult.OK) return;
 pictureBox1.Image = ;
 imgPath = ofd.FileName;
 pictureBox1.Image = new Bitmap(imgPath);
 }
 /// <summary>
 /// 直方图均衡化
 /// </summary>
 /// <param name="sender"></param>
 /// <param name="e"></param>
 private void button2_Click(object sender, EventArgs e)
 {
if (imgPath == "") return;
 Mat mat = Cv2.ImRead(imgPath, ImreadModes.Grayscale);
 Cv2.EqualizeHist(mat, mat);
 pictureBox2.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(mat);
 }
 /// <summary>
 /// 自适应的直方图均衡化
 /// 将整幅图像分成很多小块，然后再对每一个小块分别进行直方图均衡化，最后进行拼接
 /// </summary>
 /// <param name="sender"></param>
 /// <param name="e"></param>
 private void button3_Click(object sender, EventArgs e)
 {
if (imgPath == "") return;
 Mat mat = Cv2.ImRead(imgPath, ImreadModes.Grayscale);
 CLAHE clahe = Cv2.CreateCLAHE(10.0, new OpenCvSharp.Size(8, 8));
 clahe.Apply(mat, mat);
 pictureBox2.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(mat);
 }
 /// <summary>
 /// 全局直方图处理
 /// 全局直方图处理通过对 RGB 图像的 R、G、B 三层通道分别进行直方图均衡化，再整合到新的图像的方式进行。
 /// </summary>
 /// <param name="sender"></param>
 /// <param name="e"></param>
 private void button4_Click(object sender, EventArgs e)
 {
if (imgPath == "") return;
 Mat mat = Cv2.ImRead(imgPath);
 Mat[] mats = Cv2.Split(mat);//拆分
 //Mat mats0 = mats[0];//B
 //Mat mats1 = mats[1];//G
 //Mat mats2 = mats[2];//R
 Cv2.EqualizeHist(mats[0], mats[0]);
 Cv2.EqualizeHist(mats[1], mats[1]);
 Cv2.EqualizeHist(mats[2], mats[2]);
 Cv2.Merge(new Mat[] { mats[0], mats[1], mats[2] }, mat);
 pictureBox2.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(mat);
 }
 /// <summary>
 /// 局部直方图处理
 /// 即自适应直方图均衡化
 /// </summary>
 /// <param name="sender"></param>
 /// <param name="e"></param>
 private void button5_Click(object sender, EventArgs e)
 {
if (imgPath == "") return;
 CLAHE clahe = Cv2.CreateCLAHE(6.0, new OpenCvSharp.Size(8, 8));
 Mat mat = Cv2.ImRead(imgPath);
 Mat[] mats = Cv2.Split(mat);//拆分
 clahe.Apply(mats[0], mats[0]);//B
 clahe.Apply(mats[1], mats[1]);//G
 clahe.Apply(mats[2], mats[2]);//R
 Cv2.Merge(new Mat[] { mats[0], mats[1], mats[2] }, mat);
 pictureBox2.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(mat);
 }
 /// <summary>
 /// 直方图
 /// </summary>
 /// <param name="sender"></param>
 /// <param name="e"></param>
 private void button6_Click(object sender, EventArgs e)
 {
if (imgPath == "") return;
 Mat lena = Cv2.ImRead(imgPath);
 Mat[] mats = Cv2.Split(lena);//一张图片，将lena拆分成3个图片装进mat
 Mat[] mats0 = new Mat[] { mats[0] };//B
 Mat[] mats1 = new Mat[] { mats[1] };//G
 Mat[] mats2 = new Mat[] { mats[2] };//R
 Mat[] hist = new Mat[] { new Mat(), new Mat(), new Mat() };//一个矩阵数组，用来接收直方图,记得全部初始化
 int[] channels = new int[] { 0 };//一个通道,初始化为通道0
 int[] histsize = new int[] { 256 };//初始化为256箱子
 Rangef[] range = new Rangef[1];//一个通道，范围
 range[0] = new Rangef(0, 256);//从0开始（含）,到256结束（不含）
 Mat mask = new Mat();//不做掩码
 Cv2.CalcHist(mats0, channels, mask, hist[0], 1, histsize, range);//对被拆分的图片单独进行计算
 Cv2.CalcHist(mats1, channels, mask, hist[1], 1, histsize, range);//对被拆分的图片单独进行计算
 Cv2.CalcHist(mats2, channels, mask, hist[2], 1, histsize, range);//对被拆分的图片单独进行计算
 Cv2.Normalize(hist[0], hist[0], 0, 256, NormTypes.MinMax);// 归一化
 Cv2.Normalize(hist[1], hist[1], 0, 256, NormTypes.MinMax);// 归一化
 Cv2.Normalize(hist[2], hist[2], 0, 256, NormTypes.MinMax);// 归一化
 double minVal0, maxVal0;
 Cv2.MinMaxLoc(hist[0], out minVal0, out maxVal0);
 double minVal1, maxVal1;
 Cv2.MinMaxLoc(hist[1], out minVal1, out maxVal1);
 double minVal2, maxVal2;
 Cv2.MinMaxLoc(hist[2], out minVal2, out maxVal2);
 double minVal = Math.Min(minVal0, Math.Min(minVal1, minVal2));
 double maxVal = Math.Max(maxVal0, Math.Max(maxVal1, maxVal2));
 int height = 512;
 int width = 512;
 hist[0] = hist[0] * (maxVal != 0 ? height / maxVal : 0.0);
 hist[1] = hist[1] * (maxVal != 0 ? height / maxVal : 0.0);
 hist[2] = hist[2] * (maxVal != 0 ? height / maxVal : 0.0);
 Mat histImage = new Mat(height, width, MatType.CV_8UC3, new Scalar(100, 100, 100));
 int binW = (int)((double)width / histsize[0]);
for (int i = 0; i < histsize[0]; i++)
 {
 histImage.Rectangle(
 new OpenCvSharp.Point(i * binW, histImage.Rows - (int)hist[0].Get<float>(i)),
 new OpenCvSharp.Point((i + 1) * binW, histImage.Rows),
 new Scalar(255, 0, 0),
 -1);
 histImage.Rectangle(
 new OpenCvSharp.Point(i * binW, histImage.Rows - (int)hist[1].Get<float>(i)),
 new OpenCvSharp.Point((i + 1) * binW, histImage.Rows),
 new Scalar(0, 255, 0),
 -1);
 histImage.Rectangle(
 new OpenCvSharp.Point(i * binW, histImage.Rows - (int)hist[2].Get<float>(i)),
 new OpenCvSharp.Point((i + 1) * binW, histImage.Rows),
 new Scalar(0, 0, 255),
 -1);
 }
 pictureBox2.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(histImage);
 //Cv2.ImShow("hist", histImage);
 }
 /// <summary>
 /// 画面对比度调整
 /// 此处需要注意的是采用了YCrCB格式，该格式的Y通道是亮度，对其调整，实际上调整的是对比度，不会导致图片本身的失真。
 /// </summary>
 /// <param name="sender"></param>
 /// <param name="e"></param>
 private void button7_Click(object sender, EventArgs e)
 {
if (imgPath == "") return;
 Mat lena = Cv2.ImRead(imgPath, ImreadModes.Color);
 Mat yCbCR = new Mat();
 Cv2.CvtColor(lena, yCbCR, ColorConversionCodes.BGR2YCrCb);
 Mat[] channels = Cv2.Split(yCbCR);//一张图片，将lena拆分成3个图片装进mat
 Cv2.EqualizeHist(channels[0], channels[0]);
 Cv2.Merge(channels, yCbCR);
 Mat result = new Mat();
 Cv2.CvtColor(yCbCR, result, ColorConversionCodes.YCrCb2BGR);
 pictureBox2.Image = OpenCvSharp.Extensions.BitmapConverter.ToBitmap(result);
 //Cv2.ImShow("origin", lena);
 //Cv2.ImShow("EqualizeHist", result);
 }
 }
}