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Hello Friends,

What is normalization(for image and a signal)?
What I understand is for eg a signal x = [1 3 5 7 9 11].

1) Is it norm_x = x/sum(x) or norm_x = x/sum(|x|). If it is abs values of x, why is it so?

2) In case of images how do I approach this task? Should I first take the normalization of rows and then follow it with that of columns? Or would normalization of rows serve my purpose? Is it then necessary to move into column processing? Would it involve dividing of each pixel by the sum of the row(relevant0 or by the whole image sum?

3) What is the need/use and application of normalization. What data can I get from image normalization?

Regards,
Vinod Karuvat. 
0
Reply Vinod 3/4/2010 10:37:23 AM

See related articles to this posting


On 04.03.2010 11:37, Vinod wrote:
> Hello Friends,
>
> What is normalization(for image and a signal)?
> What I understand is for eg a signal x = [1 3 5 7 9 11].
>
> 1) Is it norm_x = x/sum(x) or norm_x = x/sum(|x|). If it is abs values
> of x, why is it so?
>
> 2) In case of images how do I approach this task? Should I first take
> the normalization of rows and then follow it with that of columns? Or
> would normalization of rows serve my purpose? Is it then necessary to
> move into column processing? Would it involve dividing of each pixel by
> the sum of the row(relevant0 or by the whole image sum?
>
> 3) What is the need/use and application of normalization. What data can
> I get from image normalization?
>

Dear Vinod,

Normalization is a process in which you scale input signal to a full 
range of output signal. Thus if your input is in=[0 0.5 10] and output 
range is range=[-1,1] you want your input data to be linearly scaled so 
that the min(normalize(in))=-1 and max(normalize(in))=1.
For this reason none of the formulas you provided will perform 
normalization in the sense as it is widely understood.
One of many possible approaches to signal normalization in Matlab is:
scale = (max(in)-min(in))/(range(2)-range(1));
out = in*scale;
out = out+range(1)-min(out);

2) You should perform image normalization collectively on rows and 
colums at the same time (of course, unless you want to perform separate 
normalization of each row/column). The code above should also work well 
with 2D matrices after replacing max(in) with max(max(in)) (the same 
with min) to find the maximum/minimum value in your matrix.

3) I guess you should do some background reading before starting your 
work. There are many answers, depending on the application where you 
normalize your data. In image processing you may want to do that to 
improve image contrast.

-- 
Robert
0
Reply Robert 3/4/2010 2:02:38 PM
comp.soft-sys.matlab 203819 articles. 539 followers. Post

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