I am trying to sum over my image (it is a 128x128 Uint8) in MATLAB (just a simple for loop), however, my sum will only go up to a value of 255. Afterwords it just keeps displaying 255 over and over again.
Does this mean that my variable has been assigned a Uint8 or something? If so how do I change this?
Cheers!
Yes, presumably your data is of type Uint8. But you don't have to loop to sum, just use the sum function. Assuming your data is in x:
total = sum(double(x(:)))
sum will operate over a single dimension, so if you just passed it double(x) directly, it would return a 1x128 matrix; here we have passed it all the data reshaped to a single-dimension vector (using (:)), which has been converted to double using the double function.
Note that the type of your variable will be displayed along with its name and size in the Workspace window.
Related
So what I need to do is to apply an operation like
(x(i,j)-min(x)) / max(x(i,j)-min(x))
which basically converts each pixel value such that the values range between 0 and 1.
First of all, I realised that Matlab saves our image(rows * col * colour) in a 3D matrix on using imread,
Image = imread('image.jpg')
So, a simple max operation on image doesn't give me the max value of pixel and I'm not quite sure what it returns(another multidimensional array?). So I tried using something like
max_pixel = max(max(max(Image)))
I thought it worked fine. Similarly I used min thrice. My logic was that I was getting the min pixel value across all 3 colour planes.
After performing the above scaling operation I got an image which seemed to have only 0 or 1 values and no value in between which doesn't seem right. Has it got something to do with integer/float rounding off?
image = imread('cat.jpg')
maxI = max(max(max(image)))
minI = min(min(min(image)))
new_image = ((I-minI)./max(I-minI))
This gives output of only 1s and 0s which doesn't seem correct.
The other approach I'm trying is working on all colour planes separately as done here. But is that the correct way to do it?
I could also loop through all pixels but I'm assuming that will be time taking. Very new to this, any help will be great.
If you are not sure what a matlab functions returns or why, you should always do one of the following first:
Type help >functionName< or doc >functionName< in the command window, in your case: doc max. This will show you the essential must-know information of that specific function, such as what needs to be put in, and what will be output.
In the case of the max function, this yields the following results:
M = max(A) returns the maximum elements of an array.
If A is a vector, then max(A) returns the maximum of A.
If A is a matrix, then max(A) is a row vector containing the maximum
value of each column.
If A is a multidimensional array, then max(A) operates along the first
array dimension whose size does not equal 1, treating the elements as
vectors. The size of this dimension becomes 1 while the sizes of all
other dimensions remain the same. If A is an empty array whose first
dimension has zero length, then max(A) returns an empty array with the
same size as A
In other words, if you use max() on a matrix, it will output a vector that contains the maximum value of each column (the first non-singleton dimension). If you use max() on a matrix A of size m x n x 3, it will result in a matrix of maximum values of size 1 x n x 3. So this answers your question:
I'm not quite sure what it returns(another multidimensional array?)
Moving on:
I thought it worked fine. Similarly I used min thrice. My logic was that I was getting the min pixel value across all 3 colour planes.
This is correct. Alternatively, you can use max(A(:)) and min(A(:)), which is equivalent if you are just looking for the value.
And after performing the above operation I got an image which seemed to have only 0 or 1 values and no value in between which doesn't seem right. Has it got something to do with integer/float rounding off?
There is no way for us to know why this happens if you do not post a minimal, complete and verifiable example of your code. It could be that it is because your variables are of a certain type, or it could be because of an error in your calculations.
The other approach I'm trying is working on all colour planes separately as done here. But is that the correct way to do it?
This depends on what the intended end result is. Normalizing each colour (red, green, blue) seperately will result in a different result as compared to normalizing the values all at once (in 99% of cases, anyway).
You have a uint8 RGB image.
Just convert it to a double image by
I=imread('https://upload.wikimedia.org/wikipedia/commons/thumb/0/0b/Cat_poster_1.jpg/1920px-Cat_poster_1.jpg')
I=double(I)./255;
alternatively
I=im2double(I); %does the scaling if needed
Read about image data types
What are you doing wrong?
If what you want todo is convert a RGB image to [0-1] range, you are approaching the problem badly, regardless of the correctness of your MATLAB code. Let me give you an example of why:
Say you have an image with 2 colors.
A dark red (20,0,0):
A medium blue (0,0,128)
Now you want this changed to [0-1]. How do you scale it? Your suggested approach is to make the value 128->1 and either 20->20/128 or 20->1 (not relevant). However when you do this, you are changing the color! you are making the medium blue to be intense blue (maximum B channel, ) and making R way way more intense (instead of 20/255, 20/128, double brightness! ). This is bad, as this is with simple colors, but with combined RGB values you may even change the color itsef, not only the intensity. Therefore, the only correct way to convert to [0-1] range is to assume your min and max are [0, 255].
I'm new to Matlab and for an assignment my professor is having the class write (complete really) a custom Matlab function for generating a histogram from a set of data. Essentially a new vector is being created, L which is being updated with the information from a 2D matrix M. The first column of L contains the information from M(i,j) and in a second column contains the count (total) of M(i,j) in the data set. I'm in need of some direction as to how to proceed next.
Below is where I'm at thus far:
function L = hist_count(M)
L = [ [0:255' zeros(256,1) ];
for i = 1:size(M,1)
for j = 1:size(M,2)
L(double(M(i,j))+1,2) = <<finish code here>>;
end
end
figure;
plot(L(:1),L(:2));
The <<finish code here>> section is where I'm stuck. I understand everything up to the point where I need to update L with the information.
Assistance is appreciated.
Note: Your initialization of your histogram L has the brackets mismatched.
Remove the second [ bracket in the code. In addition, the creation of the 0:255 vector is incorrect. Doing 0:255' transposes the single constant of 255, which means that it will still create a horizontal vector of 0:255 which will make the code fail. You should surround the creation of this vector with parantheses, then transpose that result. Therefore:
L = [ (0:255)' zeros(256,1) ];
Now onto your actual problem. Judging by your initialization of the histogram, there are 256 possible values so your input is most likely of type uint8, which means that the values in your data will only be from [0-255] in steps of 1. Recall that a histogram records the total number of times you see a value. In this case, you have a two column matrix where the first column tells you the value you want to examine and the second column tells you how many times you see that value in your data. Therefore, each row tells you which value you are examining in your data as well as how many times you have seen that value in your data. Note that the counts are all initialized to zero, so the logic is that every time you see a value, you need to access the right row corresponding to the data point, then increment that value by 1.
Therefore, the line is simply just accessing the current count and adding 1 to it... you then store it back:
L(double(M(i,j))+1,2) = L(double(M(i,j))+1,2) + 1;
M(i,j) is the value found at location (i,j) in your 2D data. The last question you have is why cast the intensity to double and add 1? You cast to double because the input may be an integer type. This means that any values that are beyond the dynamic range of the type will get saturated. Because your input is type uint8, any values beyond 255 will saturate to 255. In MATLAB, we index into rows and columns of a matrix starting at 1 and because the values will potentially start at value 0, this corresponds to row 1 of your histogram so you have to offset by 1. When we get to the most extreme case of value 255 for type uint8 for example, adding 1 to this using the native uint8 will saturate to 255, which means that the values of 254 and 255 get lumped into the same bin. Therefore, you must convert to some type that extends beyond the limits of uint8 and then you add by 1 to avoid saturation. double is usually done here as a default as it has higher precision than uint8, but any type that is higher than uint8 in precision is suitable.
I have a problem in general when Matlab is unable to work out how to logically store values of differing uint types. For example:
tempC = {uint8(5) uint16(16)}
For me, it seems logical to be able to convert this into a matrix of type integer using cell2mat(tempC), which returns
>> cell2mat(tempC)
Error using cell2mat (line 45)
All contents of the input cell array must be of the same data type.
Of course, I understand that the truncation behaviour of integers depends on the type (e.g. uint8 forces all numbers greater than 255 to be 255), however, in this case I would say it would be safe enough to output cell2mat(tempC) with uint16 type. Does anyone have any ideas on how this can be achieved in general?
cell2mat will not work if there are cells of differing types. cell2mat merges the cells together into a matrix, but matrix elements in MATLAB must all share the same type. This is fundamental to how MATLAB works with numeric matrices. If you didn't have all of the same type, then you should use cell arrays... which is what they are for.
However, one thing I can suggest is figure out the type of all of the elements in your matrix, then iterate through each cell and cast them all to be the largest precision type. You can then use cell2mat on this intermediate result to complete the conversion. However, what I have written doesn't actually require calling cell2mat in the end. You'll see later.
Something like this:
%// Get all of the possible types in the array
types = unique(cellfun(#class, tempC, 'uni', 0));
%// Figure out the largest type
vals = cellfun(#(x) double(intmax(x)), types);
[~,ind_max] = max(vals);
%// Cast all values to this type
class_max = types{ind_max};
tempC = cellfun(#(x) cast(x, class_max), tempC);
We first determine all of the possible classes that your cell array contains. We then figure out which of the types is the largest of them all. This can be done by using intmax on each of the types. intmax tells you the largest possible integer that is available for that type, so we basically choose the type that generates the largest possible integer. Take note that I had to cast to double as the output of intmax certainly does output the maximum associated for an integer type, but the output is also cast to that type. This is required so that I can combine all of these elements into an array of the same type - double.
Once we get the type producing the maximum possible integer, we then go through the cell array and cast all of the values to this type. Take note that I used cellfun for the final call which outputs a numeric array - no need to use cell2mat here. In the last line of code, I use cast to cast all of the numbers in the cell array to this type, thus achieving "coercion".
Using your example array, this is what I get, as well as what class the final array is in:
>> tempC
tempC =
5 16
>> class(tempC)
ans =
uint16
I am using MATLAB to load a text file that I want to make a sparse matrix out of. The columns in the text file refer to the row indices and are double type. I need them to be integers to be able to use them as indices for rows and columns. I tried using uint8, int32 and int64 to convert them to integers to use them to build a sparse matrix as so:
??? Undefined function or method 'sparse' for input
arguments of type 'int64'.
Error in ==> make_network at 5
graph =sparse(int64(listedges(:,1)),int64(listedges(:,2)),ones(size(listedges,1),1));
How can I convert the text file entries loaded as double so as to be used by the sparse function?
There is no need for any conversion, keep the indices double:
r = round(listedges);
graph = sparse(r(:, 1), r(:, 2), ones(size(listedges, 1), 1));
There are two reasons why one might want to convert to int:
The first, because you have data type restrictions.
The second, your inputs may contain fractions and are un-fit to be used as integers.
If you want to convert because of the first reason - then there's no need to: Matlab works with double type by default and often treats doubles as ints (for example, when used as indices).
However, if you want to convert to integers becuase of the second reason (numbers may be fractionals), then you should use round(), ceil() or floor() - whatever suits your purpose best.
There is another very good reason ( and really the primary one..) why one may want to convert indices of any structure (array, matrix, etc.) to int.
If you ever program in any language other than Matlab, you would be familiar with wanting to save memory space, especially with large structures. Being able to address elements in such structures with indices other than double is key.
One major issue with Matlab is the inability to more finely control the size of multidimensional structures in this way. There are sparse matrix solutions, but those are not adequate for many cases. Cell arrays will preserve the data types upon access, however the storage for every element in the cell array is extremely wasteful in terms of storage (113 bytes for a single uint8 encapsulated in a cell).
I just started matlab and need to finish this program really fast, so I don't have time to go through all the tutorials.
can someone familiar with it please explain what the following statement is doing.
[Y,I]=max(AS,[],2);
The [] between AS and 2 is what's mostly confusing me. And is the max value getting assigned to both Y and I ?
According to the reference manual,
C = max(A,[],dim) returns the largest elements along the dimension of A specified by scalar dim. For example, max(A,[],1) produces the maximum values along the first dimension (the rows) of A.
[C,I] = max(...) finds the indices of the maximum values of A, and returns them in output vector I. If there are several identical maximum values, the index of the first one found is returned.
I think [] is there just to distinguish itself from max(A,B).
C = max(A,[],dim) returns the largest elements along the dimension of A specified by scalar dim. For example, max(A,[],1) produces the maximum values along the first dimension (the rows) of A.
Also, the [C, I] = max(...) form gives you the maximum values in C, and their indices (i.e. locations) in I.
Why don't you try an example, like this? Type it into MATLAB and see what you get. It should make things much easier to see.
m = [[1;6;2] [5;8;0] [9;3;5]]
max(m,[],2)
AS is matrix.
This will return the largest elements of AS in its 2nd dimension (i.e. its columns)
This function is taking AS and producing the maximum value along the second dimension of AS. It returns the max value 'Y' and the index of it 'I'.
note the apparent wrinkle in the matlab convention; there are a number of builtin functions which have signature like:
xs = sum(x,dim)
which works 'along' the dimension dim. max and min are the oddbal exceptions:
xm = max(x,dim); %this is probably a silent semantical error!
xm = max(x,[],dim); %this is probably what you want
I sometimes wish matlab had a binary max and a collapsing max, instead of shoving them into the same function...