广州做外贸网站建设,c 教程如何做网站,做响应网站,网站空间哪家好直方图 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 Sy…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 namesender/param/// param namee/paramprivate 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 namesender/param/// param namee/paramprivate 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 namesender/param/// param namee/paramprivate 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 namesender/param/// param namee/paramprivate 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 namesender/param/// param namee/paramprivate 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].Getfloat(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].Getfloat(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].Getfloat(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 namesender/param/// param namee/paramprivate 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
