Ok, but that’s not what an digital image is. Images are designed to be invariant across camera capture and display hardware. The panel driver should interpret the dsp representation into an appropriate electronic pixel output.
> If you are looking to understand how your operating system will display images, or how your graphics drivers work, or how photoshop will edit them, or what digital cameras aim to produce, then it’s the point sample definition.
In medical imaging, data are often acquired using anisotropic resolution. So a pixel (or voxel in 3D) can be an averaged signal sample originating from 2mm of tissue in one direction and 0.9mm in another direction.
If black and white or some other cases, but there are typically subpixels that can make things like sparse enough text stroke transitions get 3X horizontal resolution.
So is this a cheap gotcha because I only said "my monitor" and "most screens" the first couple times and didn't repeat it a third time? It's the one labeled just "LCD".
Or are you arguing that the slightly rounded corners on the rectangles make a significant difference in how the filtering math works out? It doesn't. On a scale between "gaussian" and "perfect rectangles", the filtering for this shape is 95% toward the latter.
Well, "what a digital image is" is a sequence of numbers. There's no single correct way to interpret the numbers, it depends on what you want to accomplish. If your digital image is a representation of, say, the dead components in an array of sensors, the signal processing theoretic interpretation of samples may not be useful as far as figuring out which sensors you should replace.
> There's no single correct way to interpret the numbers
They are just bits in a computer. But there is a correct way of to interpret them in a particular context. For example 32 bits can be meaningless - or it can have an interpretation as a twos complement integer which is well defined.
If you are looking to understand how an operating system will display images, or how graphics drivers work, or how photoshop will edit them, or what digital cameras produce, then it’s the point sample definition.
> They use a physical process to attempt to determine light at a single point. That’s their model they try to approximate.
According to who?
A naked camera sensor with lens sure doesn't do that, it collects squares of light, usually in a mosaic of different colors. Any point approximation would have to be in software.
They usually do, but their software decisions are not gospel. They don't change the nature of the underlying sensor, which grabs areas that are pretty square.
> And outputs what? Just because the input is an area does not mean the output is an area.
> What it if it outputs the peak of the distribution across the area?
It outputs a voltage proportional to the (filtered) photon count across the entire area.
> If we look at a camera sensor and do not see a uniform grid of packed area elements would that convince you?
Non-uniformity won't convince me points are a better fit, but if the median camera doesn't use a grid I'll be interested in what you have to show.
> I notice you haven’t shared any criticism of the point model - widely understood by the field.
This whole comment line is a criticism of the input being modeled as points, and my criticism of the output is implied by my pixel art comment above (because point-like upscaling causes a giant blur) and also exists in other comments like this one: https://news.ycombinator.com/item?id=43777957
No, it's not. That article does not mention digital cameras anywhere. It briefly says that scanners give a gaussian, and I don't want to do enough research to see how accurate that is, but that's the only input device that gets detailed.
It also gives the impression that computer rendering uses boxes, when usually it's the opposite and rendering uses points.
We commonly use hardware like LCDs and printers that render a sharp transition between pixels without the Gibbs' phenomenon. CRT scanlines were close to an actual 1D signal (but not directly controlled by the pixels, which the video cards still tried to make square-ish), but AFAIK we've never had a display that is a 2D signal that we assume in image processing.
In signal processing you have a finite number of samples of an infinitely precise contiguous signal, but in image processing you have a discrete representation mapped to a discrete output. It's contiguous only when you choose to model it that way. Discrete → contiguous → discrete conversion is a useful tool in some cases, but it's not the whole story.
There are images designed for very specific hardware, like sprites for CRT monitors, or font glyphs rendered for LCD subpixels. More generally, nearly all bitmap graphics assumes that pixel alignment is meaningful (and that has been true even in the CRT era before the pixel grid could be aligned with the display's subpixels). Boxes and line widths, especially in GUIs, tend to be designed for integer multiples of pixels. Fonts have/had hinting for aligning to the pixel grid.
Lack of grid alignment, an equivalent of a phase shift that wouldn't matter in pure signal processing, is visually quite noticeable at resolutions where the hardware pixels are little squares to the naked eye.
I think you are saying there are other kinds of displays which are not typical monitors and those displays show different kinds of images - and I don’t disagree.
I'm saying "digital images" are captured by and created for hardware that has the "little squares". This defines what their pixels really are. Pixels in these digital images actually represent discrete units, and not infinitesimal samples of waveforms.
Since the pixels never were a waveform, never were sampled from such signal (even light in camera sensors isn't sampled along these axis), and don't get displayed as a 2D waveform, the pixels-as-points model from the article at the top of this thread is just an arbitrary abstract model, but it's not an accurate representation of what pixels are.
Well the camera sensor captures a greater dynamic range than the display or print media or perhaps even your eyes, so something has to give. If you ever worked with a linear file without gamma correction you will understand what I mean.
That's only for images coming directly from a camera. If the images were generated in another way, the idea that a pixel is a little square is sometimes ok (example, pixel art)
