Archived posting to the Leica Users Group, 1999/10/12
[Author Prev] [Author Next] [Thread Prev] [Thread Next] [Author Index] [Topic Index] [Home] [Search]Many of you have read most of this before. It was called "Things that go bump in the night." It is very long so if you are not interested, push delete now. For those that are interested. This is pretty much generalized so please don't pick at me about details. I've kept it general, mainly because anything more detailed would detract from the point. I do not claim to be an authority on all of this. It came from both the work I am doing at Photo Access (www.photoaccess.com) and from my reference library. And again, it's generalized for understandability. These are averages, not specifics. Sizes: 1 micron = size of a cell nucleus .1 micron = strands of DNA .01 micron = structure of DNA .001 micron = DNA molecule .0001 micron = 1 Angstrom 1 Angstrom = Carbon's outer electron shell wavelength of visible light = 4000 to 8000 Angstroms Current semiconductor chip geometry = .18 micron It could possibly go to .1 micron. The size of DNA strands. The average wavelength of light is 6 microns. How many of you remember when the Electron Microscope was invented. The reason it was invented was because visible light and optics had reached their limit. Visible light got in it's own way. So going to the atomic level, inventing a Scanning Electron Microscope, eliminated the visible light/optics limit. So at less than .1 micron, semiconductors will be stumbling over their molecular structure. And the wavelength of light requires certain dimensions in order to pass the ray and not cut it off like a filter. A polarizer, I believe, works at around 1.5 microns. These phenomena place size constraints on semiconductor junctions (such as photo transistors, AKA a pixel) and the light gathering "bucket" (a capacitive junction), and of course attempting to read-out the minuscule signal representing a pixel. The following discussion about the latent image is a high level overview. It by no means is definitive. Libraries are filled with volumes of the physics and chemistry of the latent image and development. The point being made here is that the silver image is produced at the atomic level. Atoms, electrons, and valence levels. To put things in perspective, the volume of an "average" silver halide grain is .0000000000001 cubic cm. Within the 10**-13 cubic centimeter grain of silver halide, there are 10 billion silver halide molecules. Exposure is affected by a photon hitting a silver halide molecule. This causes electrons, within the molecule, to change from a stable to an unstable energy level, leaving an electron deficiency in the lower level. Development is accomplished by allowing an electrolyte with redox potential (developer) to contact the silver halide crystal. An electron from the developer moves into the vacancy left by the electron that moved because of the photon hit. When the new electron moves in, the overall charge of the crystal is negative (because of the added negative electrons.) To compensate for the increased negative charge at the latent image site, positive charged interstitial silver ions move into the sites, neutralizing the charge. If enough photons hit the silver halide grain, enough electrons will move from the developer into the grain, which allow the formation silver atom aggregates. This is your image forming. In digital photography, a semiconductor capacitor stores the electrons (supplied by a battery) that a photo transistor allows in. The number of electrons stored will depend upon how much light hit the photo transistor, and for how long. Think of the photo transistor as an electron gate. The stored charge will be a "voltage level." This voltage (at each individual pixel site) is then applied to an analog to digital converter (A to D). The output of the A to D is a number between 0 and 255, representing the amount of light hitting the pixel. And don't forget, these pixels are read out "one at a time". All one, two, four, or six million of them. So now, in digital, we have 256 possible density levels, at a site that is at least 5 microns by 5 microns square. While in film, we have a grain site that has 10 Billion molecules. If it takes 1,000 silver atoms to produce a developed "speck" on the film, we have 10,000 possible density/size levels producible at a silver grain site. If it takes 10,000 silver atoms to produce a developed "speck" on the film, we have 1000 possible density/size levels producible at a silver grain site. All done at the atomic level. Without batteries, capacitors, transistors, A/D's, wires, megabytes of memory, gigabytes of storage, etc... By the way, it takes only takes a cluster of three silver atoms to produce a developable and detectable (not with your naked eye) speck. There's more. Each pixel in a digital sensor, sees light a little differently than its neighboring pixel. If you took a photograph using a raw sensor, it would look awful. In a good digital camera, "each" sensor has to be calibrated. We have to test and "record" how each pixel differs from a normal pixel. This is called PRNU (Photo Response Non Uniformity) correction. Cheap digital cameras (under $2000) use only "white balance" and approximately adjust each pixel's output with regard to white. Good digital systems use PRNU correction. The PRNU correction table for a 2 megapixel sensor, without PRNU compression, is six megabytes. So your professional digital camera has to have six to twenty megabytes of memory available just for pixel correction. This correction has to be done, on the fly, as pixels are streaming out of the sensor, into memory. Many digital cameras use sensors that have bad pixels. It is very difficult to make a large (35mm size) sensor without faults. That's why most consumer cameras use very tiny sensors and 10mm to 15mm lenses as the normal lens. The process of fabricating a large sensor is extremely complex and full of problems. As it is with any large semiconductor "chip". Good large sensors are very expensive to make and expensive to purchase. So bad pixels must be handled in the camera. Algorithms that give weighted averages to "previous" pixels go into forming a density value for the bad pixel. We can only use "previous" pixels because this process works as the pixels stream in, and the only known values are from "previous" pixels. Since a digital image is simply samplings of the subject, at precise points, fine patterns in the subject will be recorded incorrectly. The digitizing of anything has a "nyquest" sampling boundary where the frequency of the source (subject) interferes with the digitized output. Think of using a digital sensor for astronomical photography. Two distant stars, side by side, that happen to focus on adjacent digital pixels. The digital system will see them as a single elongated spot. Not two distinct spots, or stars, as they would appear on film. Going from analog to digital in any discipline, causes problems that didn't exist before. The real world is an analog world. Anytime you digitize any analog representation, something will be lost. That's the physics of A to D. As the sampling rate increases, the representation of the analog source is more true. Unfortunately, the sampling rate in a digital sensor is simply how closely packed and how small the pixel sensors can be made. Well... the physics of semiconductor manufacturing, pretty much establishes the rules. And we are up against the wall. END PART ONE Jim