# Thread: [Award Winner] Bitmapped Images - The technical side of things explained.

1. So I wonder if anyone would care to explain some of the operations that can be performed on an image? What does Multiply mean in terms of the color space? What do the different "Other" filters in Photoshop do (high pass, maximum, minimum, and custom. I think most of us have figured out offset)?

And once again, RR, thank you very much for this thread. I just refreshed myself on it and learned almost as much the second time through as I did the first time.

2. I found this yesterday when I started trying to translate Ascension's atlas tutorial into gimp. Since PS has a set of blend modes gimp doesn't have, this was very useful. It has a pretty detailed explanation of what each mode means (multiply, etc.), but I don't think it includes the "others."

http://en.wikipedia.org/wiki/Blend_modes

3. Good link there Gidde and I think that covers most of the modes. Theres a minimum and a max which I didnt see. Thats where you take two images and pick the pixel from either one or the other depending on whether its red, green or blue value is brightest between the two or darkest - done on a per component basis so if one had high green and low blue then it takes the green value from one and blue from the other and result is the RGB value with that green and blue in it. Same in reverse for minimum.

By treating an image with pixel values from 0 to 255 as brightness, divide those integer values by 255 to get a real value between 0.0 and 1.0 and most of the math is done like that and per component basis and then the final image is those resultant math ops then multiplied by 255 to get back to one byte per component RGB again.

So in theory you can do lots of math with images as long as you don't mind using a limited precision of 1/255 as the smallest increment. This also shows that its better to all of your math ops on images which have brightnesses across the full range. No point in doing them on limited range shades of gray like dark colors etc. Thats where some of the height banding comes from on the height mapped greyscale images you see.

4. That article does just fine up through Screen, then the details (i.e. the math) vanish. I had the same problem with the CGTextures tutorials (which I find far more enlightening than the Wikipedia article, by the way). Some of the blend modes are explained in great depth, and others just say something like
"Soft Light: Very much like Overlay, but the result is much more subtle." So what's going on in the channels that makes the effect more subtle?

5. Ahh, well the exact names that people give these things I cant help out with much. If its brightest, darkest, add, subtract, multiply, difference, invert (NOT), AND, OR, XOR. The other stuff like blur etc are not math functions but I can explain how to do those along with sharpen, emboss, edge enhancements or edge finding. But the more esoteric stuff like the buttonize, soft plastic, watercolor etc are all voodoo depending on what the programmer did. I don't think that these have exact specifications.

A lot of the non strict math stuff have a set of parameters - like the blur amount for example. In this regard soft light and hard light are algorithms that might consist of several so its a bit of a recipe or a vintage wine of taste to suit.

6. Here's a site with the math on a lot of these blend modes, and a few of his own devising.

Blend modes

7. This is a paper and some results of a new collaboration between two researchers, one from a university and one from microsoft. The results are very impressive:

http://www.geekosystem.com/depixelat...art-algorithm/

some interactive samples of it.

http://research.microsoft.com/en-us/...omparison.html

I think I just found the best free enlarger out there:

http://imageenlarger.sourceforge.net/

Here are some samples of the little image enlarged to 800% with the 4 enlarging presets (all png to avoid jpg artifacts):
Default:

Sharp:

Painted:

Sharp and Noisy:

And as a special treat, a jpeg of the samesource image blown up with the default setings to 3000%:

-Rob A>

9. Another paper outlining a new way of doing similar. Dont know much about it but you can compare by clicking on the buttons. It looks good to me with a few instances where its breaking down compared to the bicubic but not many. Also, I have to say that some of these images seem to lend itself to the algorithm. Interesting zebra pic but without a high res version of the original its not possible to note whether the leg of the zebra with stripes has been corrupted and then fixed up into something visually appealing but still incorrect. Hard to say...

http://www.wisdom.weizmann.ac.il/~vi...leImageSR.html

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