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📜  Java DIP-拉普拉斯算子

📅  最后修改于: 2020-12-14 05:43:17             🧑  作者: Mango

拉普拉斯算子也是一种导数运算符，用于查找图像中的边缘。拉普拉斯算子和其他运算符(例如Prewitt，Sobel，Robinson和Kirsch)之间的主要区别在于，它们都是一阶导数掩码，而拉普拉斯算子是二阶导数掩码。

我们使用OpenCV函数filter2D将Laplacian运算符应用于图像。可以在Imgproc软件包下找到。其语法如下-

filter2D(src, dst, depth , kernel, anchor, delta, BORDER_DEFAULT );

函数参数描述如下-

Sr.No. Arguments
1

src

It is source image.
2

dst

It is destination image.
3

depth

It is the depth of dst. A negative value (such as -1) indicates that the depth is the same as the source.
4

kernel

It is the kernel to be scanned through the image.
5

anchor

It is the position of the anchor relative to its kernel. The location Point (-1, -1) indicates the center by default.
6

delta

It is a value to be added to each pixel during the convolution. By default it is 0.
7

BORDER_DEFAULT

We let this value by default.

除了filter2D()方法之外，Imgproc类还提供其他方法。他们简要描述-

Sr.No. Method & Description
1

cvtColor(Mat src, Mat dst, int code, int dstCn)

It converts an image from one color space to another.
2

dilate(Mat src, Mat dst, Mat kernel)

It dilates an image by using a specific structuring element.
3

equalizeHist(Mat src, Mat dst)

It equalizes the histogram of a grayscale image.
4

filter2D(Mat src, Mat dst, int depth, Mat kernel, Point anchor, double delta)

It convolves an image with the kernel.
5

GaussianBlur(Mat src, Mat dst, Size ksize, double sigmaX)

It blurs an image using a Gaussian filter.
6

integral(Mat src, Mat sum)

It calculates the integral of an image.

例

下面的示例演示如何使用Imgproc类将Laplacian运算符应用于灰度图像。

import org.opencv.core.Core;
import org.opencv.core.CvType;
import org.opencv.core.Mat;

import org.opencv.highgui.Highgui;
import org.opencv.imgproc.Imgproc;

public class convolution {
   public static void main( String[] args ) {
   
      try {
         int kernelSize = 9;
         System.loadLibrary( Core.NATIVE_LIBRARY_NAME );
         
         Mat source = Highgui.imread("grayscale.jpg",  Highgui.CV_LOAD_IMAGE_GRAYSCALE);
         Mat destination = new Mat(source.rows(),source.cols(),source.type());

         Mat kernel = new Mat(kernelSize,kernelSize, CvType.CV_32F) {
            {
               put(0,0,0);
               put(0,1,-1)
               put(0,2,0);

               put(1,0-1);
               put(1,1,4);
               put(1,2,-1);

               put(2,0,0);
               put(2,1,-1);
               put(2,2,0);
            }
         };          
         
         Imgproc.filter2D(source, destination, -1, kernel);
         Highgui.imwrite("output.jpg", destination);
         
      } catch (Exception e) {
         System.out.println("Error: " + e.getMessage());
      }
   }
}

输出

当您执行给定的代码时，将看到以下输出-

原始图片

应用拉普拉斯算子教程

原始图像与拉普拉斯负运算符卷积，如下所示：

拉普拉斯负数

0 -1 0
-1 4 -1
0 -1 0

卷积图像(拉普拉斯负片)

应用拉普拉斯算子教程

原始图像使用拉普拉斯正运算符子进行卷积，如下所示：

拉普拉斯正数

0 1 0
1 -4 1
0 1 0

卷积图像(拉普拉斯正)

应用拉普拉斯算子教程