On Friday, June 16, 2017 at 11:59:15 AM UTC+2, Nikola Vitas wrote:
> On Thursday, June 15, 2017 at 12:18:49 PM UTC+1, Helder wrote:
>> Hi,
>> I couldn't find anything on this in previous posts, but I think (hope) that there's an easy solution to it.
>> I want to create a colored image out of a subset of images that are "labelled regions", that is:
>> image[0] has patches with values 1l, zero otherwise.
>> image[1] has patches with values 2l, zero otherwise.
>> ...and so on
>>
>> Typically I'm dealing with n images, where n<10. Fortunately, all images have the same dimensions.
>> I want to join the images so that the color o each [i,j] pixel is dependent on which and how many images (from the subset) had this value different from zero.
>> Example:
>> [i0,j0] is only different from zero in image[0], so it will be, e.g., red.
>> [i1,j1] is only different from zero in image[1], so it will be, e.g., blue.
>> [i1,j1] is different from zero only in image[0] and image[1], so it will be, red+blue=magenta.
>>
>> I know how to handle the pixels, any clue how to programmatically handle the colors?
>>
>> [I was thinking of using something like number conversion from basis-to-basis. That is if I have n images, I will assign to each pixel the following value:
>> [i,j] = image_0[i,j]*n^0 + image_1[i,j]*n^1 + image_2[i,j]*n^2 +... and then use a long number for indexing colors (24-bit)... but I think/hope that there is a nicer/cleaner way of doing this]
>>
>> Thanks,
>> Helder
>
> If I understand your problem, the first part is how to combine your images into one where the value of each pixel shows how many of the images have non-zero value at that location. Something like
>
> Images:
>
> 1 0 0 0 2 0 0 0 3 1 1 1
> 0 1 0 0 2 0 0 3 0 - combined -> 0 3 0
> 0 1 0 0 0 2 3 0 0 1 1 1
>
> If that's what you want to do then the quickest way is to sum up the binary maps (assuming that images stored in one 3D variable images = FLOAT(nx, ny, nimages)
>
> combined = INTARR(nx, ny)
> FOR i = 0, nimages-1 DO combined += images[*, *, i] EQ i
>
> (or i+1 or whatever else you have as indicator).
>
> Once you create the combined image, you want to display it with only nimages colors. For that you need to create a new color scale. Every color scale has 3 arrays (representing R, G and B channels) with 256 values each. For you only the first nimages values of each array will matter. The details will depend on which routine you use for displaying the data.
>
> Regarding the choice of colors, check:
> http://colorbrewer2.org/
> http://www.idlcoyote.com/ng_tips/brewer.html
Hi,
sorry for not being able to explain better...
Your suggested solution will not distinguish, for example, the following case:
image Nr --> 1 2 3 4
image-------> 001 020 030 004
combine-----> 022
I want to be able to distinguish between "1+4" and "2+3"
I'm using Superchromix's solution for the moment. After adapting and fighting a bit, I got that to work.
Thanks anyway!
Helder
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