This function measures the relative degree of focus of an image. Several up-to-date focus measuring algorithms have been implemented and the function supports uint8 or double images. For futher details on each focus measuring algorithm the reader is referred to  and the references therein. For further information and datasets, see https://sites.google.com/view/cvia/focus-measure
 S. Pertuz et al., Analysis of focus measure operators for shape-from-focus. Pattern Recognition, 46(5):1415:1432, 2013.
very useful. Thanks.
TENV algorithm is the best (for HEK cells on glass coverslip)
Extremely useful. My only feedback - many of the methods require 2D images. I ended up wrapping the code in a try-catch block. If the function fails on the initial image I throw a warning and then call the function body with rgb2gray(I) for the image input.
Hi , I want to test my image so i got your code.
but i don't know how can i use that. how do i process your code?
Thanks @Joel Cottrell for spotting this bug! The problem has been fixed
This is a very useful function for quickly trying out a range of focus measures, thank you.
Is there possibly a bug in the AcMomentum function, on line 245? It seems like the mean of the image shouldn't be multiplied by 255, because it is already in the 0-255 range (not 0.00-1.00).
If SFRQ is computed, the gradient components are initialized with the image. This yields overly high focus measure values at right and bottom image borders. I suggest to initialize both gradient components with zeros.
DCTE and DCTR return exclusively NaN for inputs of type double (haven't tried uint8 inputs).
@Anthony, the normalization is not strictly necessary since the operations are performed in double precision. However, your suggestion is quite correct if we want to avoid stability issues. I have corrected the code accordingly, thanks!
Thanks for providing your code!
Concerning the GDER criterion, I wonder wether the divisions in l 80/81 should not be replaced by
Gx = Gx / max(max(abs(Gx))) (resp. Gy)
in order to normalize the kernels?
The symmetry of the kernels implicates sum(Gx(:)) -> 0 thus creating extremely high values in resulting Gx & Gy (order of 10^13).
Sorry if I completely missed the point!
In your implementation of Brenners metric there seems to be a bug. diff(Image,2,1) and diff(Image,2,2) is used. This is somewhat like calculating the second order discrete derivation but shouldn't it be the (~first order) difference between two pixels with a distance d=2?
Sayonics.com seems to have gone away.
Thanks very much :)
How do you choose WSize=15 and sig=N/2.5 in 'GDER'? If anyone can help I would appreciate it.
Thank you for providing your code.
Very helpful, allows you to try quickly many different methods and see what suits your case.
There is for sure a small bug in SFIL case, between 270 and 315 degrees, R(:,:,7) appears twice instead of R(:,:,7) and R(:,:,8)
It seems like some of the metrics (options) needs Wavelet Toolbox (if there is something like this?), because a lot of functions for WAVS, WAVV and WAVR are missing.
Moreover, it is not exactly clear if an image should be of type uint8 or double or what - however results of some metrics depends on datatype of image.
Quite a useful tool to measure various focus measures.
I was wondering how you got the plot.
Great tool, exactly what I was looking for!
Note that the ACMO method as written also requires the Fixed-Point Toolbox. I just commented out the isdouble() check, and make sure my images are uint8 before passing them in.
Fixed a bug in the function AcMomentum
- Description updated
- Bug fixed in GDER focus operator
- Some bugs have been fixed (Brenner's and GDER's focus measure operators)
- The function no longer requires the floating-point toolbox.
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