最小值滤波 (C 语言实现)
遇到最小值滤波的问题，小白不知道。一个程序写了三天,最终今天傍晚出来了。
。。
非常easy的for循环。可是没有理解最小值滤波。怎么写都是错啊~
这是我见过做好的描写叙述，关于最小值滤波：
3*3的像素点阵，对于中心点做最小值滤波的话，它的值将从77变换到0
处理结果图：
我一直支持也坚持开源分享的原则。为大家更好的相互学习，给出源码
/******************************************************************
code writer : EOF
code date : 2014.08.07
e-mail : jasonleaster@gmail.com jasonleaster@163.com
code purpose:
This demo is coded for mininum value filter.
If you find something wrong with my code, please touch me by e-mail.
Thank you.
*******************************************************************/
#include "opencv2/highgui/highgui_c.h"
#include "opencv2/imgproc/imgproc_c.h"
#include <stdio.h>
/*------------------------------------------------------------------------------
This two Macro are used for debugging, if you are begginer with OpenCV,
it will help you to know and test what inside of the data struture in OpenCV
-------------------------------------------------------------------------------*/
//#define RGB_TEST_DEBUG
//#define CHANNEL_TEST_DEBUG
/* the offset of three channel RGB */
#define RED_BIT 2
#define GREEN_BIT 1
#define BLUE_BIT 0
#define SQUARE_LENGTH 15
int get_dark_imagine(IplImage* const img_origin,IplImage* const img_win_dark);
int main(int argc,char* argv[])
{
char* win_name_bf = "Before Processing";
char* win_name_af = "After Processing";
CvSize size;
IplImage* img_origin = cvLoadImage(argv[1],CV_LOAD_IMAGE_COLOR);
size.height = img_origin->height;
size.width = img_origin->width;
IplImage* img_win_dark = cvCreateImage(size,IPL_DEPTH_8U,1);//single channel
get_dark_imagine(img_origin,img_win_dark);
cvNamedWindow(win_name_bf,CV_WINDOW_AUTOSIZE);
//cvNamedWindow is a function which would help you to creat a window.
cvShowImage(win_name_bf,img_origin);
//Obviously, show the picture that you inputed.
cvNamedWindow(win_name_af,CV_WINDOW_AUTOSIZE);
//cvNamedWindow is a function which would help you to creat a window.
cvShowImage(win_name_af,img_win_dark);
//Obviously, show the picture that you inputed.
cvWaitKey(0);
//pause and let the user see the picture.
cvReleaseImage(&img_origin);
cvReleaseImage(&img_win_dark);
//Finally, release the struture, otherwise, memory leak !
return 0;
}
int get_dark_imagine(IplImage* const img_origin,IplImage* const img_win_dark)
{
/*
Varible description:
@img_origin : A pointer which point to the original picture's IplImage-structure.
@img_win_dark: A pointer which point to the dark-window's IplImage-structure.
*/
if(img_origin == NULL || img_win_dark == NULL)
{
printf("Error! img_origin or img_win_dark is NULL
");
return 1;
}
int height_origin = img_origin->height ;
int width_origin = img_origin->width ;//the search band width.
unsigned char * const ptr_array_origin = (unsigned char*)img_origin->imageData;
unsigned char * const ptr_array_win_dark = (unsigned char*)img_win_dark->imageData;
unsigned char* ptr_header_origin = NULL;
int row = 0;
int col = 0;
int square_row = 0;
int square_col = 0;
int min = 0;
int T_min = 0;
int temp_R = 0;
int temp_G = 0;
int temp_B = 0;
int temp = 0;
int search_win_start = SQUARE_LENGTH/2;
/*
define two varible -- height_origin & width_origin for up band-width of the search-window
*/
int search_win_height_end = img_win_dark->height - SQUARE_LENGTH/2;
int search_win_width_end = img_win_dark->width - SQUARE_LENGTH/2;
//initializition of the picture's data that 'ptr_array_win_dark' point to.
for(row = 0; row < height_origin; row++)
{
for(col = 0; col < width_origin ;col++)
{
*(ptr_array_win_dark + col + row*(img_win_dark->widthStep)) = 255;
}
}
//Mininum value filter
for(row = search_win_start; row < search_win_height_end; row++)
{
for(col = search_win_start; col < search_win_width_end ;col++)
{
ptr_header_origin = ptr_array_origin + (row)*(img_origin->widthStep) + (col)*3;
temp_B = *(ptr_header_origin + BLUE_BIT );
temp_G = *(ptr_header_origin + GREEN_BIT );
temp_R = *(ptr_header_origin + RED_BIT );
min = (temp_G < temp_B) ? temp_G : temp_B;
min = (min < temp_R) ? min : temp_R;
T_min = min;
for(square_row = (row - search_win_start); square_row < (row + search_win_start + 1);square_row++)
{
for(square_col = (col - search_win_start); square_col < (col+search_win_start + 1);square_col++)
{
min = *(ptr_array_win_dark + square_col + square_row*(img_win_dark->widthStep));
if (min > T_min)
{
*(ptr_array_win_dark + square_col + square_row*(img_win_dark->widthStep)) = (T_min);
}
}
}
}
}
return 0;
}
如有错误。欢迎交流指正
—— EOF
update : 2014.10.05
写了一个matlab版本号的最小滤波算法框架
Img_filted = dark_channel;
for row = 1 : height
for col = 1 : width
min_value = dark_channel(row,col);
for patch_row = (row -floor(search_win_height/2)) : (row + floor(search_win_height/2))
for patch_col = (col - floor(search_win_width/2)) : (col + floor(search_win_width/2))
if patch_row > 0 && patch_col > 0 && patch_row <= height && patch_col <= width
if min_value < Img_filted(patch_row,patch_col)
Img_filted(patch_row,patch_col) = min_value;
end
end
end
end
end
end