Author should've mentioned how the first image "as my camera’s sensor sees it" was obtained.

Your Christmas tree has anorexia?

Very interesting, pity the author chose such a poor example for the explanation (low, artificial and multicoloured light), making it really hard to understand what the "ground truth" and expected result should be.

>Our perception of brightness is non-linear.

Apart from brightness, it's everything. Loudness, temperature, etc.

Really enjoyed the article, thanks! A small nit - I think you have a small mistake in the value range at the start - 136000 should probably be 13600?

Maybe it’s just me but I took one look at the unprocessed photo (the first one) and immediately knew it was a skinny Christmas tree.

I’ve been staring at 16-bit HDR greyscale space for so long…

I work with camera sensors and I think this is a good way to train some of the new guys, with some added segments about the sensor itself and readout. It starts with raw data, something any engineer can understand, and the connection to the familiar output makes for good training.

see also: https://vas3k.com/blog/computational_photography/

> As a result of this, if the linear data is displayed directly, it will appear much darker then it should be.

Then -> than? (In case the author is reading comments here.)

> 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.