It is not clear to me what you want to do. Do you want to merge the data (values) together? Do you want to show the two images on top of each other (the success here would very much depend on what the images contain)? Do you want to show the two images next to each other in the same graph? Or do you want to concatenate the data of the two images in to a 2-layer 3D wave? Please be a bit more specific.
If I'm right in thinking you want an overlay of the two images, there's a couple things I like to do in this situation, depending on the data.
Chozo's suggestion to concatenate could create a single RGB image if you make it a 3 layer image, and assign each of your images of interest to the R, G, or B layers.
For more flexibility in how your images get colorized -- if your images have structure to them, you can apply a threshold to each image, and set the values that are less than that threshold to be transparent. So in your the Modify Image Appearance dialog, you would set the 'First Color' to be whatever you want the threshold to be, and in the 'Before First Color' group box, check the 'Transparent' checkbox.
Alternatively, you could manually filter the data by setting any value below a threshold to nan, and then plotting the images, like this:
myImage = (myImage < THRESHOLD_VALUE) ? nan : myImage
The attached image of two neurons overlaid on top of each other (well, ok one neuron that was rotated to make this point) uses this method to see both channels at once.
Another possibility is to create a custom color table that has transparency to make the two images semi-transparent. This would involve using the `ColorTab2Wave` operation to retrieve an existing color table, and adding a fourth column to that wave that holds transparency values. You can then apply this color wave in the dialog in the 'Color Mode' section in the bottom left, and selecting 'Color Table Wave'
It is not clear to me what you want to do. Do you want to merge the data (values) together? Do you want to show the two images on top of each other (the success here would very much depend on what the images contain)? Do you want to show the two images next to each other in the same graph? Or do you want to concatenate the data of the two images in to a 2-layer 3D wave? Please be a bit more specific.
March 26, 2024 at 02:41 am - Permalink
If I'm right in thinking you want an overlay of the two images, there's a couple things I like to do in this situation, depending on the data.
Chozo's suggestion to concatenate could create a single RGB image if you make it a 3 layer image, and assign each of your images of interest to the R, G, or B layers.
For more flexibility in how your images get colorized -- if your images have structure to them, you can apply a threshold to each image, and set the values that are less than that threshold to be transparent. So in your the Modify Image Appearance dialog, you would set the 'First Color' to be whatever you want the threshold to be, and in the 'Before First Color' group box, check the 'Transparent' checkbox.
Alternatively, you could manually filter the data by setting any value below a threshold to nan, and then plotting the images, like this:
myImage = (myImage < THRESHOLD_VALUE) ? nan : myImage
The attached image of two neurons overlaid on top of each other (well, ok one neuron that was rotated to make this point) uses this method to see both channels at once.
Another possibility is to create a custom color table that has transparency to make the two images semi-transparent. This would involve using the `ColorTab2Wave` operation to retrieve an existing color table, and adding a fourth column to that wave that holds transparency values. You can then apply this color wave in the dialog in the 'Color Mode' section in the bottom left, and selecting 'Color Table Wave'
March 26, 2024 at 08:45 am - Permalink
Two other options that were not mentioned above:
1. Use ImageBlend. The operation was designed for this task.
2. Consider displaying the two images in Gizmo. Gizmo allows you to have flexibility in applying colors/transparency to objects.
AG
March 27, 2024 at 09:29 am - Permalink