w褶积矩阵、二值化旧图经核矩阵得到新图。

https://docs.gimp.org/en/plug-in-convmatrix.html

8.2. Convolution Matrix

8.2.1. Overview

Here is a mathematician's domain. Most of filters are using convolution matrix. With the Convolution Matrix filter, if the fancy takes you, you can build a custom filter.

What is a convolution matrix? It's possible to get a rough idea of it without using mathematical tools that only a few ones know. Convolution is the treatment of a matrix by another one which is called “kernel”.

The Convolution Matrix filter uses a first matrix which is the Image to be treated. The image is a bi-dimensional collection of pixels in rectangular coordinates. The used kernel depends on the effect you want.

GIMP uses 5x5 or 3x3 matrices. We will consider only 3x3 matrices, they are the most used and they are enough for all effects you want. If all border values of a kernel are set to zero, then system will consider it as a 3x3 matrix.

The filter studies successively every pixel of the image. For each of them, which we will call the “initial pixel”, it multiplies the value of this pixel and values of the 8 surrounding pixels by the kernel corresponding value. Then it adds the results, and the initial pixel is set to this final result value.

A simple example:

On the left is the image matrix: each pixel is marked with its value. The initial pixel has a red border. The kernel action area has a green border. In the middle is the kernel and, on the right is the convolution result.

Here is what happened: the filter read successively, from left to right and from top to bottom, all the pixels of the kernel action area. It multiplied the value of each of them by the kernel corresponding value and added results. The initial pixel has become 42: (40*0)+(42*1)+(46*0) + (46*0)+(50*0)+(55*0) + (52*0)+(56*0)+(58*0) = 42. (the filter doesn't work on the image but on a copy). As a graphical result, the initial pixel moved a pixel downwards.

Convolution Matrix的更多相关文章

  1. 卷积、卷积矩阵(Convolution matrix)与核(Kernel)

    在图像处理领域,Kernel = convolution matrix = mask,它们一般都为一个较小的矩阵: 用于:Sharpen,Blur, Edge enhance,Edge detect, ...

  2. 2D image convolution

    在学习cnn的过程中,对convolution的概念真的很是模糊,本来在学习图像处理的过程中,已对convolution有所了解,它与correlation是有不同的,因为convolution = ...

  3. 数字图像处理- 3.4 空间滤波 and 3.5 平滑空间滤波器

    3.4 空间滤波基础 • Images are often corrupted by random variations in intensity, illumination, or have poo ...

  4. [Matlab] Galois Field arrays

    Operations supported for Galois Field arrays: + - - Addition and subtraction of Galois arrays. * / \ ...

  5. Deep Learning 10_深度学习UFLDL教程:Convolution and Pooling_exercise(斯坦福大学深度学习教程)

    前言 理论知识:UFLDL教程和http://www.cnblogs.com/tornadomeet/archive/2013/04/09/3009830.html 实验环境:win7, matlab ...

  6. 【ufldl tutorial】Convolution and Pooling

    卷积的实现: 对于每幅图像,每个filter,首先从W中取出对应的filter: filter = squeeze(W(:,:,filterNum)); 接下来startercode里面将filter ...

  7. Understanding Convolution in Deep Learning

    Understanding Convolution in Deep Learning Convolution is probably the most important concept in dee ...

  8. Spark MLlib Deep Learning Convolution Neural Network (深度学习-卷积神经网络)3.1

    3.Spark MLlib Deep Learning Convolution Neural Network (深度学习-卷积神经网络)3.1 http://blog.csdn.net/sunbow0 ...

  9. Deep Learning 学习随记(七)Convolution and Pooling --卷积和池化

    图像大小与参数个数: 前面几章都是针对小图像块处理的,这一章则是针对大图像进行处理的.两者在这的区别还是很明显的,小图像(如8*8,MINIST的28*28)可以采用全连接的方式(即输入层和隐含层直接 ...

随机推荐

  1. angularjs 构建主页 内置过滤器、日期的格式化

    从构建负责管理主屏幕的 MainController 开始.在这个 MainController 控制器内,只需设置一个每秒运转一次,同时更新一个局部作用域变量的延时 angular.module(' ...

  2. 关于HashMap初始化容量问题

    使用阿里云代码规范插件扫描后出现以下提示: hashmap should set a size when initalizing,即hashmap应该在初始化时设置一个大小 在网上搜到一篇讲解(htt ...

  3. [转]C艹中的各种const总结

    Ps: 难免碰到C家族的代码 ,各种const直接搞晕,搜集各种资料备用.... ----------------------------------------------------------- ...

  4. Matlab三维绘图

    三维绘图 1 三维绘图指令 类 别 指 令 说 明 网状图 mesh, ezmesh 绘制立体网状图 meshc, ezmeshc 绘制带有等高线的网状图 meshz 绘制带有“围裙”的网状图 曲面图 ...

  5. C基础之移位操作

    因为左移操作不会导致符号位出现缺位,所以不考虑符号位,低位补0即可:右移操作会涉及到符号位出现缺位的问题,所以在有符号数的右移操作时要考虑符号位怎么补的问题. 左移操作(<<)对于无符号数 ...

  6. PHP——数组2(数组函数,二维数组,正则表达式)

    <body> <?php //数组函数 $arr=array(1,2,3,4,5,6); print_r($arr); echo "<br />"; ...

  7. AtomicReference与volatile的区别

    首先volatile是java中关键字用于修饰变量,AtomicReference是并发包java.util.concurrent.atomic下的类.首先volatile作用,当一个变量被定义为vo ...

  8. Android之SystemUI载入流程和NavigationBar的分析

    Android之SystemUI载入流程和NavigationBar的分析 本篇仅仅分析SystemUI的载入过程和SystemUI的当中的一个模块StatusBar的小模块NavigationBar ...

  9. 011杰信-创建购销合同Excel报表系列-4-建立合同货物(修改,删除):合同货物表是购销合同表的子表

    前面的一篇文章做的是修改删除,这篇文章做的是合同货物的修改和删除. 业务功能如下:

  10. c# http请求,获取非200时的响应体

    HttpWebResponse res = null; try { res = request.GetResponse() as HttpWebResponse; } catch (WebExcept ...