An 8-bit grayscale image has 256 different intensity levels in it. Black and white have specific values - 0 and 255, respectively. These pixels would probably make up only a subset of the plant and soil pixels in your image. So, calculating a black/white ratio directly will not give you what you want.

As others have mentioned, your image has to be binarized, collapsing the 256 levels to just 2 levels, in effect making all the plant pixels black and all the soil pixels white. You can then merely count the number of black (0) and white (255) pixels and calculate their ratio. To do this in ImageJ,

(1) First, go to Process>Binary>Options. Check the "Black Background" box. This is so that after the thresholding operation, pixels with value 0 are shown as black and those with 255 as white. This step is not strictly required, but it just enforces the convention: 255 = white, 0 = black.

(2) Open the Threshold tool, Image>Adjust>Threshold. Check the "Dark Background" box. You should see the brighter pixels highlighted in red. These red pixels will be mapped to white and the rest to black. Keep the higher threshold (bottom slider) at 255. Adjust the lower threshold (top slider) to a value that will highlight all (or most) of your soil pixels in red. Once you are happy with the thresholding, click on the "Apply" button and you will get a binary image.

(3) Go to Edit>Selection>Create Selection. This will select only the white pixels. Go to Analyze>Measure.This will measure the selection and give a read-out in a "Results" window. The 'Area' value is the number of white (255) pixels. These are your soil pixels.

(4) Go to Edit>Selection>Make Inverse. This will invert the selection, in effect selecting only the black pixels. Go to Analyze>Measure again, and this will add a read-out row in the Results window. The 'Area' value is the number of black (0) pixels. These are your plant pixels.

You can save the table as a .csv file and find the ratio of the 'Area' values in Excel.

Michael Sandholzer's suggestion (opening the histogram dialogue and saving the list of values) is probably quicker in practice. If you follow his suggestion, you can use steps (1) and (2) to binarize the image to your liking.

I was analyzing leaf area with Image J, maybe try to convert the image to binary file, Process-Binary-Make Binary, afterwards you can analyze the area of black part Analyze-Analyze particles (first set parameters) and if you know the total area of the image should be possible to calculate the ratio. I am also new to image J.

Another very simplistic way to do it is to look at the histogram. By pressing Crtl+H once the image is open, you'll get the histogram dialogue up. When you select list you'll get the number of pixels of each of the 256 shades of gray (in an 8bit image) - if you binarised the image, that will give you just values for 0 and 255 (black and white). You can copy those values into an Excel Sheet and by adding those two values and and get total number of pixels of the image, enabling you to easily calculate ratios.

An 8-bit grayscale image has 256 different intensity levels in it. Black and white have specific values - 0 and 255, respectively. These pixels would probably make up only a subset of the plant and soil pixels in your image. So, calculating a black/white ratio directly will not give you what you want.

As others have mentioned, your image has to be binarized, collapsing the 256 levels to just 2 levels, in effect making all the plant pixels black and all the soil pixels white. You can then merely count the number of black (0) and white (255) pixels and calculate their ratio. To do this in ImageJ,

(1) First, go to Process>Binary>Options. Check the "Black Background" box. This is so that after the thresholding operation, pixels with value 0 are shown as black and those with 255 as white. This step is not strictly required, but it just enforces the convention: 255 = white, 0 = black.

(2) Open the Threshold tool, Image>Adjust>Threshold. Check the "Dark Background" box. You should see the brighter pixels highlighted in red. These red pixels will be mapped to white and the rest to black. Keep the higher threshold (bottom slider) at 255. Adjust the lower threshold (top slider) to a value that will highlight all (or most) of your soil pixels in red. Once you are happy with the thresholding, click on the "Apply" button and you will get a binary image.

(3) Go to Edit>Selection>Create Selection. This will select only the white pixels. Go to Analyze>Measure.This will measure the selection and give a read-out in a "Results" window. The 'Area' value is the number of white (255) pixels. These are your soil pixels.

(4) Go to Edit>Selection>Make Inverse. This will invert the selection, in effect selecting only the black pixels. Go to Analyze>Measure again, and this will add a read-out row in the Results window. The 'Area' value is the number of black (0) pixels. These are your plant pixels.

You can save the table as a .csv file and find the ratio of the 'Area' values in Excel.

Michael Sandholzer's suggestion (opening the histogram dialogue and saving the list of values) is probably quicker in practice. If you follow his suggestion, you can use steps (1) and (2) to binarize the image to your liking.

I would defintely recommend you visit www.MIPAR.us.

It is very powerful and intuitive 2D/3D image analysis software written by scientists/end-users and is about to be released as a free trial on December 14th. You can sign up on the site as well as submit images/datasets to test.

There are many image analysis options available, but I think you may just find MIPAR to be something special if you give it a try!

Based on the above discussion, I developed a methodology, which is suitable for the evaluation of compound cytotoxicity. In our in vitro experiments, some drug-polymer complexes (Sample1 and Sample2) were analyzed in order to determine their cytotoxic potential on murine brain endothelial cells (cerebEND). To perform cytotoxicity analysis, I used the ImageJ software to process the micrographs (Figure 1) and to calculate the relative amount (Gray value and %) of viable cells in each sample (Figure 2). The threshold was adjusted according to the reference parameter (untreated cells).

Hello

I was hoping to piggyback on your question as I have a very similar one.  I need to count the percentage of red in poinsettias from a digital picture and was hoping to find a simple method.  I just found out about this Image J software.  Would that work for me?  I want to measure percent of coloration over time of the poinsettias.  Thank you so much.

Hi Emily,

As a start, I would try the following steps.

1) From the colour image, extract a grayscale image in which the "red" regions are brighter and the rest of the image is darker (or vice versa).

This can be done by converting the colour image to the Lab colour space and extracting the "a" component as the grayscale image.

2) Threshold the grayscale image with an appropriate value to get a binary image in which all your originally red regions are represented by a white value and the rest by a black value. Counting the number of the white pixels in the binary image will then give the area of the red regions.

These steps involve pretty common image processing tasks which should be doable using ImageJ. If you attach an example image, you might be able to get better inputs on how to achieve what you want.

Hi Emily,

I wanted to jumpy back in and recommend you look at MIPAR at http://MIPAR.us. You'll be hard pressed to find a better balance of ease-of-use and power for the kind of analysis you are looking to do.

I am always here to make a custom recipe for your exact problem, and make a video demo, which adds to MIPAR's value.

Cheers,

John

Hello,

I am interested in how to automate the procedures you described above for a person who needs to process upwards of 500 images...

Regards,

Tosin

Again, MIPAR would be incredibly helpful here. Your steps are automatically recorded as you make them, but are non destructive so that you edit the sequence any time and have the rest update. Save the recipe when it's done, load into batch processor, add images, click process. Review results in Processed Image Editor. I am here for any help or training.

It may be possible in ImageJ based on your problem, with destructive macro recording, but in my experience, will not be as pleasant or efficient a process.

Cheers,

John

HI John

can I use MIPAR aoftware to increasing resolution  of HR-TEM image ,If I can how ? 

can you help me .

Hi Diman,

Thanks for posting. Could you please message me and explain more what you mean by "increase resolution"? Are you saying you wish to filter the image to reduce noise and make the lattice easier to visualize?

You can certainly upsample the image, by pixel doubling or tripling, but that is not a real resolution increase. There are techniques out there that claim to deconvolve out the point spread function of the microscope and "artificially increase resolution", but I am always wary of those claims. This is basically just a sharpening filter. If the microscope did not resolve your features properly in the first place, you are not really going to be able to resolve those features better through image processing. Excuse the expression, but there is no free lunch.

That said, you can certainly filter out noise and make features easier to visualize, so if this is what you are after, I'd be happy to help you with that.

Cheers,

John