That is the most pathetic Christmas tree I’ve ever seen. Cool article though
Consumerism.
What an unprocessed photo looks like
331–340 of 418 posts
Re: What an unprocessed photo looks like
#332I had similar experiences working with the RAW data API's that appeared a few years ago in iOS. My photos were barely better than the stuff I would take with my old Nokia!
I have a lot of respect they manage to get pictures to get to look as good as they do on phones.
Re: What an unprocessed photo looks like
#333I 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…
Yup. I had the same revelation when I learned that many of the colors we perceive don't really "exist". The closest thing to hue in nature is wavelength, but there is no wavelength for purple, for example. The color purple is our visual system's interpretation of data (ratio of trichromatic cone cell activation). It doesn't exist by itself. It's the same reason that allows RGB screens to work. No screen has ever prod…
All colors exist. Color is not the same as wavelength, color is the human perception of a collection of one or more wavelengths of light. They are all real.
Re: What an unprocessed photo looks like
#334Earlier quoted context omitted.
Ya’ll are a gold mine. Thank you. I only knew it from my forays into computer graphics and making things look right on (now older) LCD TV’s. I pulled it from some old academia papers about why you can’t just max(uv.rgb) to do greyscale nor can you do float val = uv.r This further gets funky when we have BGR vs RGB and have to swivel the bytes beforehand. Thanks for adding clarity and history to where those weights ca…
> People don’t realize how many man hours went into those early decisions. In my "trying to hunt down the earliest reference for the coefficients" I came across "Television standards and practice; selected papers from the Proceedings of the National television system committee and its panels" at https://archive.org/details/televisionstanda00natirich/mode/... which you may enjoy. The "problem" in trying to find the NT…
This is why I love graphics and game engines. It's this focal point of computer science, art, color theory, physics, practical implications for other systems around the globe, and humanities.
I kept a journal as a teenager when I started and later digitized it when I was in my 20s. The biggest impact was mostly SIGGRAPH papers that are now available online such as "Color Gamut Transform Pairs" (https://www.researchgate.net/publication/233784968_Color_Gam...).
I bought all the GPU Gems books, all the ShaderX books (shout out to Wolfgang Engel, his books helped me tremendously), and all the GPU pro books. Most of these are available online now but I had sagging bookshelves full of this stuff in my 20s.
Now in my late 40s, I live like an old japanese man with minimalism and very little clutter. All my readings are digital, iPad-consumable. All my work is online, cloud based or VDI or ssh away. I still enjoy learning but I feel like because I don't have a prestigious degree in the subject, it's better to let others teach it. I'm just glad I was able to build something with that knowledge and release it into the world.
Re: What an unprocessed photo looks like
#335Why is the native picture (fig 1) in grayscale? or more generally why is black and white the default of signal processing? Is it just because black and white are two opposites that can be easily discerned?
It's not really grayscale. The output of an image sensor integrated circuit is a series of voltages read one after the other, that could be from –0.3 to +18 volts for example, in an order specific to the sensor's red, green and blue "pixels" arrangement. The native picture (fig 1) is the result of converting a sensor's output voltage to a series of values from black (let's say -0.3 volts for example) up to white (let's say +18 volts for example) while ignoring if they are from a red, a green or a blue image sensor "pixel".
The various "raw" camera image formats kind of work like this, they include the voltages converted to some numerical range and what each "pixels" represents for a specific camera sensor setup.
Re: What an unprocessed photo looks like
#336"No adblocker detected - consider using uBlock Origin" I am getting a real sensation of what can only be described as warm fuzzies. I may have fallen deeply in love with this blog.
And here's the blog article describing the widget: https://maurycyz.com/misc/ads/
Re: What an unprocessed photo looks like
#337Why is the native picture (fig 1) in grayscale? or more generally why is black and white the default of signal processing? Is it just because black and white are two opposites that can be easily discerned?
It's just a common default choice to represent spacial data that lacks any context on how to interpret the values chromatically. You could very well use a heatmap-like color scheme instead.
Re: What an unprocessed photo looks like
#338Earlier quoted context omitted.
> The human eye is most sensitive to green light, This argument is very confusing: if is most sensitive, less intensity/area should be necessary, not more.
Note that there are two measurement systems involved: first the camera, and then the human eyes. Your reasoning could be correct if there were only one: "the sensor is most sensitive to green light, so less sensor area is needed". But it is not the case, we are first measuring with cameras, and then presenting the image to human eyes. Being more sensitive to a colour means that the same measurement error will lead to…
Oh you are right! I’m so dumb! Of course it is the camera. To have the camera have the same sensitivity, we need more green pixels! I had my neurons off.
Thanks.
Re: What an unprocessed photo looks like
#339Earlier quoted context omitted.
Yup. I had the same revelation when I learned that many of the colors we perceive don't really "exist". The closest thing to hue in nature is wavelength, but there is no wavelength for purple, for example. The color purple is our visual system's interpretation of data (ratio of trichromatic cone cell activation). It doesn't exist by itself. It's the same reason that allows RGB screens to work. No screen has ever prod…
All colors exist. Color is not the same as wavelength, color is the human perception of a collection of one or more wavelengths of light. They are all real.
I think this very quickly gets into semantics and then philosophy to the point that it’s not really a useful thing to disagree on.
We can objectively measure the properties of the radiation reaching eyeballs and we can detect sensor differences in some eyeballs in various ways. But we can’t ever know that “red” is the same sensation for both of us.
The concept of “red” is real, made concrete by there being a word for it.
But most colours can be associated with a primary wavelength… except purple. So by that definition, they don’t really exist.
Re: What an unprocessed photo looks like
#340The site explicitly states that :
"This website is not licensed for ML/LLM training or content creation. "
Yet I asked chatgpt to summarize it , and it did. And it says that: Why summarization is allowed
In most jurisdictions and policies: Summarization is a transformative use It does not substitute for the original work It does not expose proprietary structure, wording, or data It does not enable reconstruction of the original content
very strange days, you cant cope with this mouthful mambo jambos.