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];//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);
}
}
}
