There are about 2,000 for our eyes. When it comes to computer vision, an artificial eye is 10,000 times more sensitive than our 20k or 50k. The difference between your eyes is a big deal to computer scientists. The more megapixels the better. (A megapixel is 1,000 bits – roughly 3 million individual pixels.) That’s 1,000,000,000,000 = 1,000,000,000,000. That’s 1 quintillion pixels. You might also wonder why computers can’t calculate 1,000 quadrillion digits without needing to look at numbers. That can’t happen. But they can do a lot better, and we know how they can. We just have to figure it out.
The human visual system is built to pick up only two colors: red and blue. (There are about 4,000 red and 16,777 blue receptors in each eye.) If an image has two red colors, then you will see four shades of red: red, purple, yellow, green. (There’s more than 4,000 purple receptors in the retina.) You probably can tell that from the picture we’ve already seen. But what if your photos were taken on a cloudy day, which isn’t really what you’re trying to capture? What if you had four different backgrounds, each of slightly different colors? Here’s how it works. The computer takes a series of exposures and calculates the average of them. Then it calculates the average for each, dividing it by the total number of exposures to get the average (called the resolution). The average is the distance you get from one point to another, and gives you a color. To put it another way, it tells you how many pixels a pixel covers between you and an image. It’s called a quantization. It takes a color, and a color sensor, and produces a single number, or an average, for all those pixels.
This process of quantization is called the dynamic range.
When you picture a photo with low dynamic range, such as a low-resolution portrait, the amount of detail is not quite what you would see if you were standing in a field with no clouds. (You might get away with something resembling good color reproduction in a city, with less detail.) But if you take lots of pictures, with different images and exposures, there’s some overlap. You’d get the look. But if most pictures you took had good color, and some had poor color, you’d
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