I appreciate the authors honest with their astrophotography.
What an unprocessed photo looks like
121–130 of 418 posts
Re: What an unprocessed photo looks like
#122Earlier quoted context omitted.
You can upscale a 170x170 image yourself, if you're not familiar with what that looks like. The only high frequency details you have after upscaling are artifacts. This thing pulled real details out of nowhere.
That is not true For example see https://en.wikipedia.org/wiki/Edge_enhancement
That example isn't doing any scaling.
You can try to guess the location of edges to enhance them after upscaling, but it's guessing, and when the source has the detail level of a 170x170 moon photo a big proportion of the guessing will inevitably be wrong.
And in this case it would take a pretty amazing unblur to even get to the point it can start looking for those edges.
Re: What an unprocessed photo looks like
#123But does applying the same transfer function to each pixel (of a given colour anyway) count as "processing"? What bothers me as an old-school photographer is this. When you really pushed it with film (e.g. overprocess 400ISO B&W film to 1600 ISO and even then maybe underexpose at the enlargement step) you got nasty grain. But that was uniform "noise" all over the picture. Nowadays, noise reduction is impressive, but…
Equally bad is the massive over sharpening applied to CCTV and dash cams. I tried to buy a dash cam a year ago that didn't have over sharpened images but it proved impossible.
Reading reg plates would be a lot easier if I could sharpen the image myself rather than try to battle with the "turn it up to 11" approach by manufacturers.
Re: What an unprocessed photo looks like
#124Earlier quoted context omitted.
That is not true For example see https://en.wikipedia.org/wiki/Edge_enhancement
That example isn't doing any scaling. You can try to guess the location of edges to enhance them after upscaling, but it's guessing, and when the source has the detail level of a 170x170 moon photo a big proportion of the guessing will inevitably be wrong. And in this case it would take a pretty amazing unblur to even get to the point it can start looking for those edges.
You're mistaken and the original experiment does not distinguish between classic edge aware upscaling/super resolution vs more problematic replacement
Re: What an unprocessed photo looks like
#125I love posts that peel back the abstraction layer of "images." It really highlights that modern photography is just signal processing with better marketing. A fun tangent on the "green cast" mentioned in the post: the reason the Bayer pattern is RGGB (50% green) isn't just about color balance, but spatial resolution. The human eye is most sensitive to green light, so that channel effectively carries the majority of t…
the bayer pattern is one of those things that makes me irrationally angry, in the true sense, based on my ignorance of the subject what's so special about green? oh so just because our eyes are more sensitive to green we should dedicate double the area to green in camera sensors? i mean, probably yes. but still. (⩺_⩹)
Green is in the center of the visible spectrum of light (notice the G in the middle of ROYGBIV), so evolution should theoretically optimize for green light absorption. An interesting article on why plants typically reflect that wavelength and absorb the others: https://en.wikipedia.org/wiki/Purple_Earth_hypothesis
Re: What an unprocessed photo looks like
#126Earlier quoted context omitted.
That example isn't doing any scaling. You can try to guess the location of edges to enhance them after upscaling, but it's guessing, and when the source has the detail level of a 170x170 moon photo a big proportion of the guessing will inevitably be wrong. And in this case it would take a pretty amazing unblur to even get to the point it can start looking for those edges.
You're mistaken and the original experiment does not distinguish between classic edge aware upscaling/super resolution vs more problematic replacement
I'm mistaken about which part? Let's start here:
You did not link an example of upscaling, the before and after are the same size.
Unsharp filters enhance false edges on almost all images.
If you claim either one of those are wrong, you're being ridiculous.
Re: What an unprocessed photo looks like
#127I studied remote sensing in undergrad and it really helped me grok sensors and signal processing. My favourite mental model revelation to come from it was that what I see isn’t the “ground truth.” It’s a view of a subset of the data. My eyes, my cat’s eyes, my cameras all collect and render different subsets of the data, providing different views of the subject matter. It gets even wilder when perceiving space and ti…
> My favourite mental model revelation to come from it was that what I see isn’t the “ground truth.” It’s a view of a subset of the data. My eyes, my cat’s eyes, my cameras all collect and render different subsets of the data, providing different views of the subject matter.
What a nice way to put it.
Re: What an unprocessed photo looks like
#128Earlier quoted context omitted.
If you really want that old school NTSC look: 0.3R + 0.59G + 0.11B This is the coefficients I use regularly.
Interesting that the "NTSC" look you describe is essentially rounded versions of the coefficients quoted in the comment mentioning ppm2pgm. I don't know the lineage of the values you used of course, but I found it interesting nonetheless. I imagine we'll never know, but it would be cool to be able to trace the path that lead to their formula, as well as the path to you arriving at yours
The NTSC color coefficients are the grandfather of all luminance coefficients.
It is necessary that it was precisely defined because of the requirements of backwards-compatible color transmission (YIQ is the common abbreviation for the NTSC color space, I being ~reddish and Q being ~blueish), basically they treated B&W (technically monochrome) pictures like how B&W film and videotubes treated them: great in green, average in red, and poorly in blue.
A bit unrelated: pre-color transition, the makeups used are actually slightly greenish too (which appears nicely in monochrome).
Re: What an unprocessed photo looks like
#129But does applying the same transfer function to each pixel (of a given colour anyway) count as "processing"? What bothers me as an old-school photographer is this. When you really pushed it with film (e.g. overprocess 400ISO B&W film to 1600 ISO and even then maybe underexpose at the enlargement step) you got nasty grain. But that was uniform "noise" all over the picture. Nowadays, noise reduction is impressive, but…
> For example, the IP cameras I have, sometimes when I come home on the bike, part of the wheel is missing, having been deleted by the algorithm as it struggled with the "grainy" asphalt driveway underneath.
Heavy denoising is necessary for cheap IP cameras because they use cheap sensors paired with high f-number optics. Since you have a photography background you'll understand the tradeoff that you'd have to make if you could only choose one lens and f-stop combination but you needed everything in every scene to be in focus.
You can get low-light IP cameras or manual focus cameras that do better.
The second factor is the video compression ratio. The more noise you let through, the higher bitrate needed to stream and archive the footage. Let too much noise through for a bitrate setting and the video codec will be ditching the noise for you, or you'll be swimming in macroblocks. There are IP cameras that let you turn up the bitrate and decrease the denoise setting like you want, but be prepared to watch your video storage times decrease dramatically as most of your bits go to storing that noise.
> Smartphone and dedicated digital still cameras aren't as drastic, but when zoomed in, or in low light, faces have a "painted" kind of look. I'd prefer honest noise, or better yet an adjustable denoising algorithm from "none" (grainy but honest) to what is now the default.
If you have an iPhone then getting a camera app like Halide and shooting in one of the RAW formats will let you do this and more. You can also choose Apple ProRAW on recent iPhone Pro models which is a little more processed, but still provides a large amount of raw image data to work with.
Re: What an unprocessed photo looks like
#130But does applying the same transfer function to each pixel (of a given colour anyway) count as "processing"? What bothers me as an old-school photographer is this. When you really pushed it with film (e.g. overprocess 400ISO B&W film to 1600 ISO and even then maybe underexpose at the enlargement step) you got nasty grain. But that was uniform "noise" all over the picture. Nowadays, noise reduction is impressive, but…
I hear you. Two years ago I went to my dad's and I spent the afternoon "scanning" old pictures of my grandparents (his parents), dead almost two decades ago. I took pictures of the physical photos, situating the phone as horizontal as possible (parallel to the picture), so it was as similar as a scan (to avoid perspective, reflection, etc).
It was my fault that I didn't check the pictures while I was doing it. Imagine my dissapointment when I checked them back at home: the Android camera decided to apply some kind of AI filter to all the pictures. Now my grandparents don't look like them at all, they are just an AI version.