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What an unprocessed photo looks like

maurycyz.com

181–190 of 418 posts

Re: What an unprocessed photo looks like

#181

I 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…

> modern photography is just signal processing with better marketing

I pass on a gift I learned of from HN: Susan Sunday’s “On Photography”.

Re: What an unprocessed photo looks like

#182

I 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 human eye is most sensitive to green light, so that channel effectively carries the majority of the luminance (brightness/detail) data

How does this affect luminance perception for deuteranopes? (Since their color blindness is caused by a deficiency of the cones that detect green wavelengths)

Re: What an unprocessed photo looks like

#183

Earlier quoted context omitted.

Alt + 0151, baby! Or... however you do it on MacOS. But now, likewise, having to bail on emdashes. My last differentiator is that I always close set the emdash—no spaces on either side, whereas ChatGPT typically opens them (AP Style).

On the mac you just type — for an em dash or – for an en dash.

Is this a troll?

But anyway, it’s option-hyphen for a en-dash and opt-shift-hyphen for the em-dash.

I also just stopped using them a couple years ago when the meme about AI using them picked up steam.

Re: What an unprocessed photo looks like

#184
post #101

Earlier quoted context omitted.

> 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 the luminance (brightness/detail) data. From the classic file format "ppm" (portable pixel map) the ppm to pgm (portable grayscale map) man page: https://li…

Funnily enough that's not the only mistake he made in that article. His final image is noticeably different from the camera's output image because he rescaled the values in the first step. That's why the dark areas look so crushed, eg around the firewood carrier on the lower left or around the cat, and similarly with highlights, e.g. the specular highlights on the ornaments. After that, the next most important proble…

I didn’t read the article as implying that the final image the author arrived at was “unprocessed”. The point seemed to be that the first image was “unprocessed” but that the “unprocessed” image isn’t useful as a “photo”. You only get a proper “picture” Of something after you do quite a bit of processing.

Re: What an unprocessed photo looks like

#185
post #166

Earlier quoted context omitted.

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. (⩺_⩹)

Not sure why it would invoke such strong sentiments but if you don’t like the bayer filter, know that some true monochrome cameras don’t use it and make every sensor pixel available to the final image. For instance, the Leica M series have specific monochrome versions with huge resolutions and better monochrome rendering. You can also modify some cameras and remove the filter, but the results usually need processing.…

Not to mention that there are non-Bayer cameras that vary from the Sigma Foveon and Quattro sensors that use stacked sensors to filter out color entirely differently to the Fuji EXR and X-Trans sensors.

Re: What an unprocessed photo looks like

#186
post #50

Earlier quoted context omitted.

found the guy who didn't know about em dashes before this year also your question implies a bad assumption even if you disclaim it. if you don't want to imply a bad assumption the way to do that is to not say the words, not disclaim them

The hatred mostly comes from TTS models not properly pausing for them. “NO EM DASHES” is common system prompt behavior.

You know, I didn’t think about that, but you’re right. I have seen so many AI narrations where it reads the dash exactly like a hyphen, actually maybe slightly reducing the inter-word gap. Odd the kinds of “easy” things such as complicated and advanced system gets wrong.

Re: What an unprocessed photo looks like

#187
post #112

> There’s nothing that happens when you adjust the contrast or white balance in editing software that the camera hasn’t done under the hood. The edited image isn’t “faker” then the original: they are different renditions of the same data. Almost, but not quite? The camera works with more data than what's present in the JPG your image editing software sees.

You can always edit the RAW files from the camera, which essentially means working with the same data the camera chip had to generate the JPEGs.

Not quite. At the very least, the RAW file is a static file. Whereas your camera chip can make interactive decisions.

In any case, RAW files aren't even all that raw. First, they are digitised. They often apply de-noising, digital conditioning (to take care of hot and dead pixels), lens correction. Some cameras even apply some lossy compression.

Re: What an unprocessed photo looks like

#188
I was lucky enough to take some introductory courses at the NTNU Colorlab in Gjøvik, Norway. What I learned there changed my view on vision.

Computer imaging is much wider than you think. It cares about the entire signal pipeline, from emission from a light source, to capture by a sensor, to re-emission from a display, to absorption in your eye, and how your brain perceives it. Just like our programming languages professor called us "Pythonized minds" for only knowing a tiny subset of programming, there is so much more to vision than the RGB we learn at school. Look up "Metamerism" for some entry-level fun. Color spaces are also fun and funky.

There are a lot of interesting papers in the field, and its definitely worth reading some.

A highlight of my time at university.

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