HDOJ 3359 Kind of a Blur
用高斯消元对高斯模糊的图像还原....
Kind of a Blur
Time Limit: 2000/1000 MS (Java/Others) Memory Limit: 32768/32768 K (Java/Others)
Total Submission(s): 1321 Accepted Submission(s): 383
topics in image processing. This process is called deblurring, which will be your task for this problem.
In this problem, all images are in grey-scale (no colours). Images are represented as a 2 dimensional matrix of real numbers, where each cell corresponds to the brightness of the corresponding pixel. Although not mathematically accurate, one way to describe
a blurred image is through averaging all the pixels that are within (less than or equal to) a certain Manhattan distance?
from each pixel (including the pixel itself ). Here's an example of how to calculate the blurring of a 3x3 image with a blurring distance
of 1:

Given the blurred version of an image, we are interested in reconstructing the original version assuming that the image was blurred as explained above.



<= min(W/2,H/2)). The remaining H lines specify the gray-level of each pixel in the blurred image. Each line specifies W non-negative real numbers given up to the 2nd decimal place. The value of all the given real numbers will be less than 100.
Zero or more lines (made entirely of white spaces) may appear between cases. The last line of the input file consists of three zeros.
test cases by an empty line. Do not print an empty line after the last test case. It is guaranteed that there is exactly one unique solution for every test case.
2 2 1
1 1
1 1 3 3 1
19 14 20
12 15 18
13 14 16 4 4 2
14 15 14 15
14 15 14 15
14 15 14 15
14 15 14 15 0 0 0
1.00 1.00
1.00 1.00 2.00 30.00 17.00
25.00 7.00 13.00
14.00 0.00 35.00 1.00 27.00 2.00 28.00
21.00 12.00 17.00 8.00
21.00 12.00 17.00 8.00
1.00 27.00 2.00 28.00HintThe Manhattan Distance (sometimes called the Taxicab distance) between
two points is the sum of the (absolute) difference of their coordinates.
The grid on the lower right illustrates the Manhattan distances from the grayed cell.
#include <iostream>
#include <cstdio>
#include <cstring>
#include <algorithm>
#include <cmath> using namespace std; const double eps=1e-8;
const int maxn=130; double data[maxn/10][maxn/10],a[maxn][maxn],x[maxn];
int n,m,d; int equ,val; void Gauss()
{
int k,col,mar;
for(k=0,col=0;k<equ&&col<val;k++,col++)
{
mar=k;
for(int i=k+1;i<equ;i++)
{
if(fabs(a[i][col])>fabs(a[mar][col]))
mar=i;
}
if(fabs(a[mar][col])<eps) return ;
if(k!=mar)
{
for(int i=col;i<val;i++)
swap(a[k][i],a[mar][i]);
swap(x[k],x[mar]);
}
x[k]/=a[k][col];
for(int i=col+1;i<val;i++)
a[k][i]/=a[k][col];
a[k][col]=1.;
for(int i=0;i<equ;i++)
{
if(i==k) continue;
x[i]-=x[k]*a[i][col];
for(int j=col+1;j<val;j++)
a[i][j]-=a[k][j]*a[i][col];
a[i][col]=0;
}
}
} int main()
{
bool fst=false;
while(scanf("%d%d%d",&m,&n,&d)!=EOF)
{
if(n==0&&m==0) break;
if(fst) putchar(10);
else fst=true;
memset(a,0,sizeof(a));
memset(x,0,sizeof(x));
for(int i=0;i<n;i++)
{
for(int j=0;j<m;j++)
{
scanf("%lf",&data[i][j]);
int cnt=0;
int t1=i*m+j,t2=0;
for(int ii=0;ii<n;ii++)
{
for(int jj=0;jj<m;jj++)
{
if(abs(i-ii)+abs(j-jj)<=d)
{
t2=ii*m+jj;
a[t2][t1]=1.;
cnt++;
}
}
}
x[t1]=data[i][j]*cnt;
}
}
equ=val=n*m;
Gauss();
for(int i=0;i<n;i++)
{
for(int j=0;j<m;j++)
{
printf("%8.2lf",x[i*m+j]);
}
putchar(10);
}
}
return 0;
}
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