I have this series of underexposed captures taken in low light from mixed sources like tungsten and energy saving fluorescent bulbs. Straightforward conversions were so-so and I wanted to test how Negative Lab Pro handles such takes depending on how I exposed the “scans” and what effect different border buffer widths (BBW) could produce.
Here is a “contact sheet” showing the results. Please take them with a grain of salt because of what’s in the image like candles and scarcity of different colours.
From top left per row
1.: Conversions of captures with increasing exposure (roughly 0-2 EV in thirds) and BBW=0
2.: Conversions of captures with increasing exposure (roughly 0-2 EV in thirds) and BBW=5
3.: Conversions of captures with increasing exposure (roughly 0-2 EV in thirds) and BBW=10
4.: Conversions of captures with increasing exposure (roughly 0-2 EV in thirds) and BBW=15
5.: Conversions of captures with increasing exposure (roughly 0-2 EV in thirds) and BBW=20
6.: Conversions of captures with increasing exposure (roughly 0-2 EV in thirds) and BBW=25
The widest border buffer produced bright results because the candles were cut off. Therefore, NLP adjusted the white point based on the furniture behind the person, while all other conversions targeted the flames for white points.
→ Lesson: (Cropping off) highlights can greatly influence results.
We can see colours casts and shift slightly depending on exposure and BBW. These casts/shifts follow a logic that I can currently only guess … and your guess is as good as mine …
I find the first row to be closest to what I’d want from this take. Results are fairly independent of exposure (nice) even though some colour cast creeps in and out in the series.
All things considered, I recommend to
- test systematically the “difficult” negatives of subjects that are worthwhile
- accept that conversions are starting points for post-processing, preferably on 16 bit TIFFs
- consider cropping off parts with blown highlights before converting. Redo the crop afterwards.