Opencv 均值滤波

均值滤波也称为线性滤波，其采用的主要方法为邻域平均法。线性滤波的基本原理是用均值代替原图像中的各个像素值，即对待处理的当前像素点（x，y），选择一个模板，该模板由其近邻的若干像素组成，求模板中所有像素的均值，再把该均值赋予当前像素点（x，y），作为处理后图像在该点上的灰度g（x，y），即g（x，y）=∑f（x，y）/m m为该模板中包含当前像素在内的像素总个数。

使用3\times3的均值滤波器来进行滤波吧！

均值滤波器使用网格内像素的平均值。

python实现：

import cv2
import numpy as np

# mean filter
def mean_filter(img, K_size=3):
    H, W, C = img.shape

    # zero padding
    pad = K_size // 2
    out = np.zeros((H + pad * 2, W + pad * 2, C), dtype=np.float)
    out[pad: pad + H, pad: pad + W] = img.copy().astype(np.float)
    tmp = out.copy()

    # filtering
    for y in range(H):
        for x in range(W):
            for c in range(C):
                out[pad + y, pad + x, c] = np.mean(tmp[y: y + K_size, x: x + K_size, c])

    out = out[pad: pad + H, pad: pad + W].astype(np.uint8)

    return out

# Read image
img = cv2.imread("imori.jpg")

# Mean Filter
out = mean_filter(img, K_size=3)

# Save result
cv2.imwrite("out.jpg", out)
cv2.imshow("result", out)
cv2.waitKey(0)
cv2.destroyAllWindows()

C++实现：

#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <math.h>


// mean filter
cv::Mat mean_filter(cv::Mat img, int kernel_size){
  int height = img.rows;
  int width = img.cols;
  int channel = img.channels();

  // prepare output
  cv::Mat out = cv::Mat::zeros(height, width, CV_8UC3);

  // prepare kernel
  int pad = floor(kernel_size / 2);

  // filtering
  double v = 0;
  int vs[kernel_size * kernel_size];
  int count = 0;

  for (int y = 0; y < height; y++){
    for (int x = 0; x < width; x++){
      for (int c = 0; c < channel; c++){
      v = 0;

      // get pixel sum
      for (int dy = -pad; dy < pad + 1; dy++){
        for (int dx = -pad; dx < pad + 1; dx++){
          if (((y + dy) >= 0) && ((x + dx) >= 0)){
            v += (int)img.at<cv::Vec3b>(y + dy, x + dx)[c];
          }
        }
      }

      // assign mean value
      v /= (kernel_size * kernel_size);
      out.at<cv::Vec3b>(y, x)[c] = (uchar)v;
      }
    }
  }
  return out;
}

int main(int argc, const char* argv[]){
  // read image
  cv::Mat img = cv::imread("imori.jpg", cv::IMREAD_COLOR);

  // mean filter
  cv::Mat out = mean_filter(img, 3);

  //cv::imwrite("out.jpg", out);
  cv::imshow("answer", out);
  cv::waitKey(0);
  cv::destroyAllWindows();

  return 0;
}

输入：

输出：