I have a question about intensity inhomogeneity. I read a paper, it defined a way to calculate the intensity inhomogeneity based on average filter:
Let see my problem, I have a image I (below code) and a average filter with r=3. I want to calculate image transformation J based on formula (17). Could you help me to implement it by matlab code? Thank you so much.
This is my code
%Create image I
I=[3 5 5 2 0 0 6 13 1
0 3 7 5 0 0 2 8 6
4 5 5 4 2 1 3 5 9
17 10 3 1 3 7 9 9 0
7 25 0 0 5 0 10 13 2
111 105 25 19 13 11 11 8 0
103 105 15 26 0 12 2 6 0
234 238 144 140 51 44 7 8 8
231 227 150 146 43 50 8 16 9
];
%% Create filter AF
size=3; % scale parameter in Average kernel
AF=fspecial('average',[size,size]); % Average kernel
%%How to calculate CN and J
CN=mean(I(:));%Correct?
J=???
You're pretty close! The mean intensity is calculated correctly; all you are missing to calculate J is apply the filter defined with fspecial to your image:
Here is the code:
clc
clear
%Create image I
I=[3 5 5 2 0 0 6 13 1
0 3 7 5 0 0 2 8 6
4 5 5 4 2 1 3 5 9
17 10 3 1 3 7 9 9 0
7 25 0 0 5 0 10 13 2
111 105 25 19 13 11 11 8 0
103 105 15 26 0 12 2 6 0
234 238 144 140 51 44 7 8 8
231 227 150 146 43 50 8 16 9
];
% Create filter AF
size=3; % scale parameter in Average kernel
AF=fspecial('average',[size,size]); % Average kernel
%%How to calculate CN and J
CN=mean(I(:)); % This is correct
J = (CN*I)./imfilter(I,AF); % Apply the filter to the image
figure;
subplot(1,2,1)
image(I)
subplot(1,2,2)
image(J)
Resulting in the following:
Related
This is a matrix and I want to know is it possible to show it as a tree in MATLAB?
It contains of two class (1 and 2) and every row would be a branch of a tree.
The zero in this matrix means there is nothing because of matrix length I used zero.
I used these functions on MATLAB but it seems I should write a custom one.
treeplot(A);
Matrix A:
10 13 0 1
10 13 22 1
10 22 0 1
13 22 0 1
17 26 0 1
4 12 0 2
4 12 15 2
4 15 0 2
7 12 0 2
7 12 15 2
7 15 0 2
12 15 0 2
12 15 17 2
15 17 0 2
As an example the first 4 lines of this matrix on the paper will be:
I have a matrix,DataFile=8x8. One of those columns(column 6 or "coarse event") can only be 0 or a 1. It will be 0 for a non-stable condition and 1 for a stable condition.Now for the example:
DataFile = [ 11 5 66 1.2 14.1 0 -1 0.1;...
12 6 67 1.4 15.1 0 -1 0.1;...
13 7 68 1.6 16.1 1 -1 0.2;...
14 8 69 1.7 16.5 1 -2 0.1;...
15 9 68 1.6 16.2 0 -1 0.3;...
16 8 66 1.3 15.7 1 -2 0.0;...
17 5 65 1.5 16.1 1 0 0.0;...
18 6 66 1.2 16.6 0 1 1.0];
With slight changes from the code in the comments:
DataFile =[zeros(1,size(DataFile,2)); DataFile; zeros(1,size(DataFile,2))];
startInd = [find(diff(DataFile(:,6))==1)];
endInd = [find(diff(DataFile(:,6)) <0)];
B={};
for n=1:1:numel(endInd)
B(n)={DataFile(startInd(n):endInd(n),:)};
end
FirstBlock=B{1};
SecondBlock=B{2};
The result is 2 matrices(FirstBlock=3x8,SecondBlock=3x8), which wrongfully includes 0's in the 6th column. It should be giving two matrices(dataIs1(1)=2x8 and dataIs1(2)=2x8), with only 1's in the 6th column.
In reality I would like have the a n-amount of matrices, for which the "coarse event" is 1. Thank you for the help!
The magic word is logical indexing:
If you have a Matrix A:
A=[1 2 3 4 5;...
0 6 7 8 9;...
1 7 8 9 10]
you can extact Row 1 and 2 by:
B=A(A(:,1)==1)
Hope thats waht your looking for, have fun.
To seperate the groups we need to know where they start and end:
endInd = [find(diff(A(:,1))<0) size(A,1)]
startInd = [1 find(diff(A(:,1))==1)]
Then assigne the Data to arrays:
B={};
for n=1:1:numel(endInd)
B(n)={A(startInd(n):endInd(n),:)};
end
Edit:
Your new Data:
DataFile = [ 11 5 66 1.2 14.1 0 -1 0.1;...
12 6 67 1.4 15.1 0 -1 0.1;...
13 7 68 1.6 16.1 1 -1 0.2;...
14 8 69 1.7 16.5 1 -2 0.1;...
15 9 68 1.6 16.2 0 -1 0.3;...
16 8 66 1.3 15.7 1 -2 0.0;...
17 5 65 1.5 16.1 1 0 0.0;...
18 6 66 1.2 16.6 0 1 1.0];
I add some padding to avoid mistakes:
DataFile =[zeros(1,size(DataFile,2)); DataFile; zeros(1,size(DataFile,2))]
Now, as before, we look for the starts and ends of the blocks:
endInd = [find(diff(A(:,1)) <0) -1]
startInd = [find(diff(A(:,1))==1)]
Then assigne the Data to a cell in a arrays:
B={};
for n=1:1:numel(endInd)
B(n)={A(startInd(n):endInd(n),:)};
end
If you want to retrive, say, the second block:
secondBlock=B{2};
I want to use randsample to sample values from a matrix, but I want the values sampled to be replaced by zero in the matrix. What do I do/Is there a fuction for this?
I think you don't want to use randsample because you have a given matrix (here M). You can use datasample instead to randomly sample existing data. Then you can use the second output of datasample (here ind) to address the entries in the original matrix M and overwrite them easily.
In the following example operates over the second dimension and takes a selection of columns. If you want a selection of rows, change the third argument of datasample to 1 (this is Matlab's default behaviour when no third argument is given).
% create random data
M = randi(20,4,10)
% randomly sample data
[Y,ind] = datasample(M,4,2)
% write 0 for the sampled data in original matrix
M(:,ind) = 0
This is the result:
M =
20 14 6 18 1 9 4 15 11 11
11 5 9 20 8 19 2 9 3 13
20 20 16 4 1 16 13 11 4 9
15 1 4 12 20 18 4 19 11 13
Y =
18 4 15 14
20 2 9 5
4 13 11 20
12 4 19 1
ind =
4 7 8 2
M =
20 0 6 0 1 9 0 0 11 11
11 0 9 0 8 19 0 0 3 13
20 0 16 0 1 16 0 0 4 9
15 0 4 0 20 18 0 0 11 13
Initialized with rng(4).
(For my problem, I use a matrix A 4x500000. And the values of A(4,k) varies between 1 and 200).
I give here an example for a case A 4x16 and A(4,k) varies between 1 and 10.
I want first to match a name to the value from 1 to 5 (=10/2):
1 = XXY;
2 = ABC;
3 = EFG;
4 = TXG;
5 = ZPF;
My goal is to find,for a vector X, a matrix M from the matrix A:
A = [20 52 70 20 52 20 52 20 20 10 52 20 11 1 52 20
32 24 91 44 60 32 24 32 32 12 11 32 2 5 24 32
40 37 24 30 11 40 37 40 40 5 10 40 40 3 37 40
2 4 1 3 4 5 2 1 3 3 8 6 7 9 6 10]
A(4,k) takes all values between 1 and 10. These values can be repeated and they all appear on the 4th line.
20
X= 32 =A(1:3,1)=A(1:3,6)=A(1:3,8)=A(1:3,9)=A(1:3,12)=A(1:3,16)
40
A(4,1) = 2;
A(4,6) = 5;
A(4,8) = 1;
A(4,9) = 3;
A(4,12) = 6;
A(4,16) = 10;
for A(4,k) corresponding to X, I associate 2 if A(4,k)<= 5, and 1 if A(4,k)> 5. For the rest of the value of A(4,k) which do not correspond to X, I associate 0:
[ 1 2 3 4 5 %% value of the fourth line of A between 1 and 5
2 2 2 0 2
ZX = 6 7 8 9 10 %% value of the fourth line of A between 6 and 10
1 0 0 0 1
2 2 2 0 2 ] %% = max(ZX(2,k),ZX(4,k))
the ultimate goal is to find the matrix M:
M = [ 1 2 3 4 5
XXY ABC EFG TXG ZPF
2 2 2 0 2 ] %% M(3,:)=ZX(5,:)
Code -
%// Assuming A, X and names to be given to the solution
A = [20 52 70 20 52 20 52 20 20 10 52 20 11 1 52 20
32 24 91 44 60 32 24 32 32 12 11 32 2 5 24 32
40 37 24 30 11 40 37 40 40 5 10 40 40 3 37 40
2 4 1 3 4 5 2 1 3 3 8 6 7 9 6 10];
X = [20 ; 32 ; 40];
names = {'XXY','ABC','EFG','TXG','ZPF'};
limit = 10; %// The maximum limit of A(4,:). Edit this to 200 for your actual case
%// Find matching 4th row elements
matches = A(4,ismember(A(1:3,:)',X','rows'));
%// Matches are compared against all possible numbers between 1 and limit
matches_pos = ismember(1:limit,matches);
%// Finally get the line 3 results of M
vals = max(2*matches_pos(1:limit/2),matches_pos( (limit/2)+1:end ));
Output -
vals =
2 2 2 0 2
For a better way to present the results, you can use a struct -
M_struct = cell2struct(num2cell(vals),names,2)
Output -
M_struct =
XXY: 2
ABC: 2
EFG: 2
TXG: 0
ZPF: 2
For writing the results to a text file -
output_file = 'results.txt'; %// Edit if needed to be saved to a different path
fid = fopen(output_file, 'w+');
for ii=1:numel(names)
fprintf(fid, '%d %s %d\n',ii, names{ii},vals(ii));
end
fclose(fid);
Text contents of the text file would be -
1 XXY 2
2 ABC 2
3 EFG 2
4 TXG 0
5 ZPF 2
A bsxfun() based approach.
Suppose your inputs are (where N can be set to 200):
A = [20 52 70 20 52 20 52 20 20 10 52 20 11 1 52 20
32 24 91 44 60 32 24 32 32 12 11 32 2 5 24 32
40 37 24 30 11 40 37 40 40 5 10 40 40 3 37 40
2 4 1 3 4 5 2 1 3 3 8 6 7 9 6 10]
X = [20; 32; 40]
N = 10;
% Match first 3 rows and return 4th
idxA = all(bsxfun(#eq, X, A(1:3,:)));
Amatch = A(4,idxA);
% Match [1:5; 5:10] to 4th row
idxZX = ismember([1:N/2; N/2+1:N], Amatch)
idxZX =
1 1 1 0 1
1 0 0 0 1
% Return M3
M3 = max(bsxfun(#times, idxZX, [2;1]))
M3 =
2 2 2 0 2
My data matrix is large: smt like 180:3000 size.
Each element value is between 0 to 255;
I have to find areas in this matrix where average value is higher than some threshold (lets call it 'P'). And reset each element in these areas to '0'. Another words filter my matrix.
I have width and heigth of filter area.
So I need to loop over data matrix to find appropriate areas (As many as exist).
EDIT:
Please, see an example:
4 6 7 5 6 6 7
10 8 9 8 9 10 9
10 8 9 8 9 10 9
7 4 6 9 7 8 7
4 5 5 5 5 5 5
4 5 5 5 5 5 5
10 12 12 12 13 10 11
14 15 15 16 14 15 15
13 15 15 15 14 14 13
This is given matrix. Lets try to find areas (2, 3) of size where average value is > 15.
So the result will be:
4 6 7 5 6 6 7
10 8 9 8 9 10 9
10 8 9 8 9 10 9
7 4 6 9 7 8 7
4 5 5 5 5 5 5
4 5 5 5 5 5 5
10 12 12 12 13 10 11
14 0 0 0 14 15 15
13 0 0 0 14 14 13
Please, look at bottom of matrix
Please, give me some tips how it is possible to loop throw.
Thank you very much.
One way of doint this is as follows:
% example A with more areas of mean greater than 15
% there are four such areas as shown here: http://i.imgur.com/V6m0NfL.jpg
A = [16 16 16 5 16 16 16
16 16 16 8 16 16 16
10 8 9 8 9 10 9
7 4 6 9 7 8 7
4 5 15.1 15 15 5 5
4 5 15 15 15 5 5
10 12 12 12 13 10 11
14 15 15 16 14 15 15
13 15 15 15 14 14 13];
% filter size
[n,m] = deal(2,3);
% filter center
center = floor(([n,m]+1)/2);
% find where we have areas greater than 15
B = nlfilter(A, [n,m], #(b) mean(b(:)) > 15);
% get coordinates of areas with mean > 15
[rows,cols] = find(B);
% zero out elements in all found areas
for i = 1:size(rows,1)
% calculate starting coordinates for the area to be set to 0
row = rows(i) - center(1) + 1;
col = cols(i) - center(2) + 1;
A(row:row+n-1 , col:col+m-1) = 0;
end
Results in:
A =
0 0 0 5 0 0 0
0 0 0 8 0 0 0
10 8 9 8 9 10 9
7 4 6 9 7 8 7
4 5 0 0 0 5 5
4 5 0 0 0 5 5
10 12 12 12 13 10 11
14 0 0 0 14 15 15
13 0 0 0 14 14 13
try this
a = input_matrix;
ii = 2 ; jj = 3;
threshold = 15;
x = ones(ii,jj)/(ii*jj);
%\\create matrix temp2 with average value of block a(i:i+ii-1,j:j+jj-1) at temp2(i,j)
temp1 = conv2(a,x,'full');
temp2 = temp1(ii:end-ii+1,jj:end-jj+1);
%\\find row and column indices of temp2 with value > threshold
[row_ col_] = find(temp2>threshold);
out = a;
%\\assign zero value to the corresponding blocks
for iii = 1:length(row_)
out(row_(iii):row_(iii)+ii-1,col_(iii):col_(iii)+jj-1) = 0;
end