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📜  Java DIP-应用框过滤器

📅  最后修改于: 2020-12-14 05:40:03             🧑  作者: Mango

我们应用使图像模糊的Box滤镜。 Box过滤器的尺寸可能为3×3、5×5、9×9等。

我们使用OpenCV函数filter2D将Box滤镜应用于图像。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. Argument & Description
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Box滤镜应用于灰度图像。

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 = Mat.ones(kernelSize,kernelSize, CvType.CV_32F);          
         
         for(int i=0; i

输出

当您执行给定的代码时，将看到以下输出-

原始图片

应用盒式过滤器教程

在此示例中，我们将图像与以下滤镜(内核)进行卷积。随着图像尺寸的增加，该滤镜会导致图像模糊。

该原始图像已与大小为5的盒式过滤器卷积，如下所示-

尺寸5的盒式过滤器

1/25 1/25 1/25 1/25 1/25
1/25 1/25 1/25 1/25 1/25
1/25 1/25 1/25 1/25 1/25
1/25 1/25 1/25 1/25 1/25
1/25 1/25 1/25 1/25 1/25

卷积图像(具有大小为5的框滤镜)

应用盒式过滤器教程

卷积图像(带有大小为9的Box过滤器)

应用盒式过滤器教程