Difference in two images

[Prashant Wasnik]

Respected Sir,
I am working on lipids and want to determine the difference among these
images. I have tried to measure the pixel intensities, particle analysis,
GLCM after removing Gausian blur at 25 sigma but unfortunately I not
getting the appropriate difference.  I am attaching two images for your
kind reference. Kindly suggest the methodology.
Thanking You
With Regards

--
P.G.Wasnik,
Associate Professor,
Dept of Dairy Engineering
College of Dairy Technology,
Warud (Pusad)-445 204
09900514036 Bangalore
09422866519 Maharashtra

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html

[Herbie-3]

Prashant Wasnik,

if you wish to obtain the mathematical difference of the two images then use
        Process > Image Calculator...

First convert both images to 32 bit, then use "Image Calculator..." with
"Operation" either "Difference" or "Subtract". The former mode results
in an image containing the absolute value of the difference of both
images. Finally, you may convert the result image to 8 bit.

HTH

Herbie

:::::::::::::::::::::::::::::::::::::::::
On 02.02.14 08:37, Prashant Wasnik wrote:
> Respected Sir,
> I am working on lipids and want to determine the difference among these
> images. I have tried to measure the pixel intensities, particle analysis,
> GLCM after removing Gausian blur at 25 sigma but unfortunately I not
> getting the appropriate difference.  I am attaching two images for your
> kind reference. Kindly suggest the methodology.
> Thanking You
> With Regards

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html

[Leon Espinosa-3]

Dear Prashant, maybe what you want is a method to quantify de difference between two conditions based on the images... so the problem is what "parameter" of the image is measuring the difference that you want to show. It seems it is not the intensity, but one of the image seem more "flat" and the other more rougher. The variance of the image could be a clue : transform the images in 32-bits (Image/Type), apply the variance filter (Process/Filters/Variance/ with the good radius i.e. around the size of structures) select the whole image and measure the mean intensity (= the value of the mean variance). In my hands with a radius = 10 I obtained 1251 vs. 824

I hope it helps...

Leon



Le 2 févr. 2014 à 08:37, Prashant Wasnik a écrit :

> Respected Sir,
> I am working on lipids and want to determine the difference among these
> images. I have tried to measure the pixel intensities, particle analysis,
> GLCM after removing Gausian blur at 25 sigma but unfortunately I not
> getting the appropriate difference.  I am attaching two images for your
> kind reference. Kindly suggest the methodology.
> Thanking You
> With Regards
>
> --
> P.G.Wasnik,
> Associate Professor,
> Dept of Dairy Engineering
> College of Dairy Technology,
> Warud (Pusad)-445 204
> 09900514036 Bangalore
> 09422866519 Maharashtra
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> <G33005gCBC.tif><Go3005gCBC.tif>

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html

[Prashant Wasnik]

Thanks for kind help. I will let you know the results.
On Feb 4, 2014 4:06 PM, "Leon Espinosa" <[hidden email]> wrote:

> Dear Prashant, maybe what you want is a method to quantify de difference
> between two conditions based on the images... so the problem is what
> "parameter" of the image is measuring the difference that you want to show.
> It seems it is not the intensity, but one of the image seem more "flat" and
> the other more rougher. The variance of the image could be a clue :
> transform the images in 32-bits (Image/Type), apply the variance filter
> (Process/Filters/Variance/ with the good radius i.e. around the size of
> structures) select the whole image and measure the mean intensity (= the
> value of the mean variance). In my hands with a radius = 10 I obtained 1251
> vs. 824
>
> I hope it helps...
>
> Leon
>
>
>
> Le 2 févr. 2014 à 08:37, Prashant Wasnik a écrit :
>
> > Respected Sir,
> > I am working on lipids and want to determine the difference among these
> > images. I have tried to measure the pixel intensities, particle analysis,
> > GLCM after removing Gausian blur at 25 sigma but unfortunately I not
> > getting the appropriate difference.  I am attaching two images for your
> > kind reference. Kindly suggest the methodology.
> > Thanking You
> > With Regards
> >
> > --
> > P.G.Wasnik,
> > Associate Professor,
> > Dept of Dairy Engineering
> > College of Dairy Technology,
> > Warud (Pusad)-445 204
> > 09900514036 Bangalore
> > 09422866519 Maharashtra
> >
> > --
> > ImageJ mailing list: http://imagej.nih.gov/ij/list.html
> > <G33005gCBC.tif><Go3005gCBC.tif>
>
> --
> ImageJ mailing list: http://imagej.nih.gov/ij/list.html
>

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html

[Cammer, Michael]

As a proxy for contrasty edges, how about for each image:
run("Gaussian Blur...", "sigma=1");
run("Gaussian Blur...", "sigma=2");
run("Variance...", "radius=5");
Threshhold and count white pixels.

===========================================================================
Michael Cammer, Microscopy Core & Dustin Lab , Skirball Institute, NYU Langone Medical Center
Cell:  914-309-3270   Lab: 212-263-3208
http://ocs.med.nyu.edu/microscopy & http://www.med.nyu.edu/skirball-lab/dustinlab/


-----Original Message-----
From: ImageJ Interest Group [mailto:[hidden email]] On Behalf Of Prashant Wasnik
Sent: Sunday, February 02, 2014 2:38 AM
To: [hidden email]
Subject: Difference in two images

Respected Sir,
I am working on lipids and want to determine the difference among these images. I have tried to measure the pixel intensities, particle analysis, GLCM after removing Gausian blur at 25 sigma but unfortunately I not getting the appropriate difference.  I am attaching two images for your kind reference. Kindly suggest the methodology.
Thanking You
With Regards

--
P.G.Wasnik,
Associate Professor,
Dept of Dairy Engineering
College of Dairy Technology,
Warud (Pusad)-445 204
09900514036 Bangalore
09422866519 Maharashtra

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html

------------------------------------------------------------
This email message, including any attachments, is for the sole use of the intended recipient(s) and may contain information that is proprietary, confidential, and exempt from disclosure under applicable law. Any unauthorized review, use, disclosure, or distribution is prohibited. If you have received this email in error please notify the sender by return email and delete the original message. Please note, the recipient should check this email and any attachments for the presence of viruses. The organization accepts no liability for any damage caused by any virus transmitted by this email.
=================================

--
ImageJ mailing list: http://imagej.nih.gov/ij/list.html