X-Trans demosaic algorithms differences

Started 6 months ago | Discussions thread
saltydogstudios Regular Member • Posts: 232
Re: X-Trans demosaic algorithms differences

WOW. Thank you so much for posting these samples.

I've gained so much insight from pixel peeping these images. Would you be OK with me using these images in my blog ? I'll credit you however you like.

The blog is just a way for me to capture long-form thoughts that don't quite fit a forum, especially if those thoughts might need to go back and be edited for precision. It's hosted on a free platform & I make no money from it.

So my initial theory was that wormies were caused by increased microcontrast - but I was only partly right.

Wormies are also caused by the *regularity* of the X-Trans sensor. A sensor that we were told was more random than bayer.

Exhibit A

Three versions of the image. I've highlighted a 4x4 grid across each so you have a reference point.

Processed completely in Raw Therapee.

Left image - raw sensor data.

Middle image - "3 pass" demosaicing. Look at the regularity of the up & down lines above the highlighted area.

Right image - using the "Microcontrast" filter in Raw Therapee set to max to create wormies.

No other edits, except taking into Photoshop to crop, enlarge & create the 4x4 contrast section.

Exhibit B

Just to be sure, I re-ran this using Adobe - and true to my theory the 2x2 interior grids created more areas of microcontrast - but also the 4x4 outer grids are a big part of the "wormies" noise pattern.

So my theory was perhaps half right - wormies are caused by the 2x2 green grids creating greater microcontrast... But it's the interaction of the 2x2 green green grids and the straight-line red/blue pixel grids (4x4 that surround the 2x2 green grids) that interact to create the wormies.

"Detail" (aka microcontrast) algorithms look for "straight" lines - areas that are obviously brighter vs. adjacent areas that are darker - the definition of microcontrast. The Fuji X-Trans sensor works against these algorithms in two specific ways.

a) the 2x2 green pixel grids create areas of great microcontrast, increasing that contrast creates small "L" shaped wormies.

b) the "straight line" "outer" red and blue pixel grids create areas of straight-line contrast with the "inner" green grids, that the algorithms pick up on as straight lines in the image that actually only exist on the sensor. Increasing that contrast creates longer straight-line wormies.

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