My source is http://www.photographyblog.com/reviews/ They have a very large collection of raws, often with matching jpgs, from a multitude of cameras. The images I used for this tutorial shows a family group at the end of a subway corridor that are almost lost in the darkness and ISO128000 noise. A challenging shot that will showcase several RT tools.
The link for the jpg--we will compare the RT results with the straight out of the camera results--is
http://img.photographyblog.com/reviews/panasonic_lumix_dmc_g7/sample_images/panasonic_lumix_dmc_g7_36.jpg The matching raw file is panasonic_lumix_dmc_g7_36.rw2
If you haven't upgraded to the windows build RT 4.2.269 or mac RT 4.2.270 do so immediately. If you are working with wavelets any earlier build will disappoint. Build 269 is stable (no crashes in about a week) and has several new features and bug fixes (a beta release for RT 4.3 maybe) plus some new documentation.
Jacques, the chief developer behind wavelets and CIECAM has posted an updated RawPedia article in french. I'm sure is makes great reading if you are fluent in technical french, but after going through google translates the meaning has been mangled in some sections. Example, when you come to a confusing sentence about a 'beach' the correct translation is 'range' as in range of values. But for the most part it is understandable and in this tutorial I will try to expand on what you will learn there
Wavelets are 3 dimensional. This mathematical third dimension is one of the reasons you see three sliders in many sub tools; two of which will confuse you because they seem to do nothing or make the image worse, Some reasons for this behavior are:
1- they work much better with a different type of image
2-they are in the tool because Jacques and team have future surprises planned
3-they are there because Jacques and team hopes we users will come up with some of the new surprises.
So if you hit a slider or curve that confuses you leave it at the defaults. They have been carefully chosen to work with the majority of images.
Enough talk, the workflow: Lets see what we can do with this image
This is the matching jpg to the raw file we will use, ISO 12800 and SOOTC, The goal is to create as decent an image as possible of the family group that are barely visible at the end of the subway tunnel without completely destroying the detail by the handrail in the foreground
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I started with the the residual image tool. It got its name because it was what was left over after the calculations extracted the wavelets. What you do to the wavelets doesn't change it. And vice versa. You must recombine them either on your RT screen in real time in a 100% view or after a trip to the queue. That's one disadvantage when developing wavelet workflows. To chase down all the smal artifacts I develop test jpgs at key steps so I can look at them with other programs. Such as imageJ, a widely used and free NIH scientific image analysis program.
You can modify the residual image with non wavelet tools. The shadow and highlight sliders lighten or darken their areas of the images. Their matching threshold sliders decides how large an area they effect. In past tutorials I recommenced using CIECAM for contrast and chroma because of the tool's curves. Now with the new final tuneup curves ...you pays your penny and takes your pick.
With this image the shadow slider brightens the family group so I can see how bad the noise is.
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It is ISO12800 bad, clearly what Jacques calls high noise in his rawPedia article. I'm pleased that the noise reduction workflow I touched on in my Lorde tutorial is now his recommended workflow. In the program flow the preliminary noise reduction in the second tab is now before the color conversion step. The wavelet denoise is now at the end and is intended to clean up any additional noise and artifacts created by sharpening and other adjustments.
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For the noise preclean I chose Lum 70 and Detail 30. Depending on the final results I can fine tune these numbers.
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To lighten the back area more I tone mapped the image. While wavelet tone mapping is less aggressive and more artifact free than RT's earlier version when it is combined with its gamma slider it can lighten and darken to both extremes.
It's worth mentioning that tone mapping works on the signal side of the all important signal to noise ratio just as noise reduction works on the noise side. RT tone mapping uncovers noise in dark areas. It doesn't create it. We are prone to saying the new full frame camera we bough to collect more light the light in its bigger pixels makes less noisy images, Instead, when the exposure collects four times the light-- four times greater signal-- that is combined with twice the noise to double the signal to noise ratio. This may sound like super geek nit picking but I've seen forum discussions go off the rails into making wrong claims when people didn't understand or take into account the difference. A recent claim I've seen that tone curve also causes noise is one example.
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To bring back the sharpness lost with the initial noise reductions I used edge sharpening with edge detection checked. That sub tool tames edge sharpening. The first slider, gradiant sensitivity, determines the amount of taming, The second noise slider checks for nearby noise. With low ISO images it has no effect; with high ISO images it increases the sharpening and can create artifacts. The last slider depends on the image and the other settings and can increase or decrease sharpness.
I followed my own advice and used the default values in the subtool. I set the sharpness, changed first level to unchanged and dragged out another contrast curve before I pulled up a 300 % view for a good look at the increased noise.
If it had been much worst I might have increased the Lum settings. Instead I went to wavelet denoise
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A combination of denoise and impulse noise reduction from the second detail tab--combining the two is a class 3 tip --cleaned up real noise exposed by sharpening and a few L shaped artifacts visible in 300% view. Since the goal of this workflow was to fix the darkest area in a ISO12800 image we have to live with some loss of sharpening.
I left the bottom denoise slider at zero. Ever since I began working with wavelet I wondered why anyone would add a slider that increased the noise to a noise reduction algorithm. Jacques latest RawPedia article explained all. Take a 30sec dark night image and the slider brings out the stars in all their glory. Another example of what seems useless or worse with one type of images my be very useful with another quite different type.
The developers didn't include all the sliders in a big joke to confuse us users. They all have a purpose and it's our job to work out the neat little photo tricks they allow.
In his RawPedia article Jacques also cautions about not expecting decent results if you use a saved pp3 on a different image. On this I think he is being over cautious. If you use a saved pp3 that was perfect for a close up of a rose in bright sunlight on one of the ninety concert hall stage shots of your favorite pop-rock band you won't be happy. But if you develop one of the stage shots and use it in the file browser to develop the other 89 stages shots you are well on the way towards fine tuning the three perfect shots you will post and brag about on your Facebook page.
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I used a parameter curve in the new Fine Tune tool to even out the lighting in the corridor, Now the histogram is bunched up in the center and needs to be expanded for a better black to white contrast range. So I went to CIECAM.
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CIECAM contrast and a touch of colorfullness fixed the problem, So how did we do?
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Photographybogs.com's untouched camera jpg vs RT's greatly improved jpg.
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A roughly neutral grey S/N improvement from about 10 to almost a 100...
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at the cost of a very slight loss of contrast--see the lines on the meter--that no one would notice if the two images weren't shown side by side.
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A scaled down version (for the blog) of the original photographyblog jpg and the RT jpg. If you aren't impressed you must be working for an enemy big bucks image editor company. (grin)
