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

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 = null;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];//RCv2.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]);//Bclahe.Apply(mats[1], mats[1]);//Gclahe.Apply(mats[2], mats[2]);//RCv2.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matMat[] mats0 = new Mat[] { mats[0] };//BMat[] mats1 = new Mat[] { mats[1] };//GMat[] mats2 = new Mat[] { mats[2] };//RMat[] 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0int[] 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matCv2.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);}}
}

Demo下载