What exactly is a negative image and why does the negative of normal seem to be only blue and white?


What exactly is a negative image and why does the negative of normal seem to be only blue and white?

In: Biology

Negative images take place back in time, when photography was argentic. It was the original picture taken on the photosensitive film, with “reverse colors”, you had to project it on argentic paper (silver tinctured paper) and processed it through chemical bath to reveal the picture. The colors on negative images are the opposite to what you’re seeing for real. I white appears black, black is white, skin tones are bluish… And so on… It have something to do with light absorption and reflection.

Your eyes have three sets of rods and cones, one which detects red light, one which detects blue light, and one which detects green light. All colors we see are perceived as signals based on the amount it excites the chemicals in those rods and cones. However there is a maximum amount that each of those rods and cones can be excited, as well as a minimum. For ease of demonstration I will set the scale as 0 to 258 (because that’s what conputers use to simulate it). So if a color is signified by the excitation levels of 100-150-25 then it’s “negative” is 258 minus those values or 158-138-233.

It’s only going to be blue and white if the original image is more red or your screen/photo has a colour tint.

You can look at a negative image as one where you have replaced the colour with It’s opposite. Its probably easier to envisage in digital form tjsm photographic film terms but either is valid. For a black and white image with black = 0 and white = 255 then to get a negative image you replace the brightness B of each pixel with 255-B. So full black (B=0) becomes full white (B=255) and so on.

You can do the same with a colour image. If you are working in RGB coordinates you just replace each one with 255 minus it’s value. So, for instance, an orange colour R=255, G=63, B=0, will become a greenish blue R=0, G=192, B=256.

You still have the full range of colours available so there is no inherent bias towards blue in that process.