This is the same picture with with RT 5.4 It seems to solve the issue!
But I did not take the time to make it as good as you did @Morgan_Hardwood. Incidentaly, is any .pp3 file compatible across various PC / OS ? If yes, could you send me yours so that I would try it on the RAW file, please ?
@pierpiotr the PP3 is compatible with all matching versions of RT regardless of operating system. I already attached it in my previous post. I used a development version of RT-5.4 but it should look fine in RT-5.4 stable.
Hmm … there is still aliasing present … look AT 300% magnification at the top right corner during editing with RT with your pp3.
It comes from interaction of
pixelation present in raw values … This comes from RAW channel imbalance. In monochrome shots, normaly all channels (R,G1,B,G2) should give equal statistics … but here we have strong inbalance and the bad thing is that it is not consistend across the frame … it’s slight at the center … worse at the corners … and the worst is at the top right …
the slight rotation of 1.25°
With the use of sharpening and/or some arbitrary resampling ratios this can become visible at normal magnifications …
pier, if you have time available please shoot some flat frames* … this will give us reliable data regarding the channel imbalances … and there is strong possibility that applying flat field correction will correct all of them at the appropriate degree … maybe with a bit of tuning of the flat field algorithm …
*use a lens with no or negligible vignette, disable any vignette correction setting in camera, choose a flat featureless-non textured surface homogeneously lit, tune the focus point so that your surface is strongly out of focus, shoot it
@heckflosse Ingo, I am searching for a way to separately scale G1 data because in the sample file I detected a mismatch around 4% …
The green equilibration has little or no effect here (I suppose it operates an averaging …)
The statistics are
R = 1.00 (it’s the most sensitive)
G2 = 1.00 (varies netween 0.99 - 1.01)
G1 = 0.96 (varies in 0.95 - 0.97)
B = 0.92 (0.94 at the left - 0.88 ar the right)
I’d like to normalize G1 to 1.00 then the WB will be more effective to normalize B …
The only way that comes to my mind is to manipulate the per channel camconst WhiteLevels … and I am not sure if this will work …
I asked for flat frames as pier provided (well almost ) to correct the non homogenuity of the (supposed) blue pixels … and indeed this does a good jod …
pitty that RT doesn’t give the option to adjust separatelly the G1 vs G2 channels
Or use a green equalization (G1 vs G2) routine based on flat field data …
Either way … because by coincidense the green imbalance is consistent, if the user additionally to flat frame corrections, adds a bit of green equilibration (set at 5.0) everything gets better … no more vertical and horizontal texture …
no worry @Morgan_Hardwood I had not started shooting 60+ white pix yet.
To make sure I understand you guys right :
Clipped images are not necessary because they are needed to set up a camera profile and it already exists in RT for the Sony A6000
@ilias_giarimis asked for flat frames so that he could suggest a setting in RT like [quote=“ilias_giarimis, post:30, topic:5335”] green equilibration (set at 5.0) [/quote] that alleviates the defects seen in my pictures
If for some readers my comment sounds wrong … they are right
Because at the start the result with mono was worse than expected and then … I forgot to mension that I used a different technique … instead of mono demosaic I used none + all values at 95 in channel mixer. This way the auto and spot WB work, and using a bit of green equilibration + the flat field correction eliminates any pattern
See none + channel mixer against mono …