I prepared a scene-referred starting point by merging the RAW files with HDRMerge and saving a neutral processing in linear Rec.2020
I saved the following exposure steps from the HDRMerge output: -1, 0, +1, +2, +3
from the scene-referred version I saved 5 images at different exposure values (from -1EV to +3V with respect to CRW_3012.DNG), which were then processed with enfuse. The enfuse output looks flat, but provides a compressed dynamic range with limited suppression of the local contrast.
I took other three images, then followed the exact outlined steps, and then opened the enfuse output in Darktable. The problem is that I can’t properly handle the highlights, that is, I’m not able to recover detail in the sky. There’s only a big white sky.
Regarding the shadows, everything is ok, and I get much better results in tone mapping than I would if I was working with a non-compressed image.
What am I doing wrong? Isn’t this workflow applicable to any image? Shouldn’t I be able to manipulate the compressed information in the highlights as I do in the shadows?
As a side note, I also tried working with different exposure values in the enfuse step, like -2, -1, 0, +1, +2, and -3, -2, -1, 0, +1, but then I couldn’t get the same results in the shadows and, although I could recover more detail in the highlights, I still couldn’t achieve the contrast I’m aiming at.
The issue is your use of enfuse and expectation of highlight recovery.
If you read the enfusemanual, you would see that there is much that you could do with it, including choosing which parts to include via masking and alpha.
If I recall correctly, your raw files were on the dark side. You can only recover what is there to begin with and not create something out of nothing. When you have multiple frames, you have more data. But more data where? In your case, the data density is still in the shadows. Hence, it makes no sense to export other exposure value sets from HDRMerge. In fact, you only export exposures where the various regions of your image look right.
Some photographers don’t approach it this way. They take creative license and synthesize or replace the sky altogether.
PS If you would like to gain more experience working with highlights, try tackling this [PlayRaw] 4: the Irish musician. Try to balance the light and retain detail in the lights. It took me a few tries and my highlight management skills improved as a result.
I don’t know exactly what you mean but my guess is that the two images are very different in terms of content, contrast and proportion. Using only the defaults is like opening a raw processor and doing nothing. That won’t work for every photo.
If you are still following @Carmelo_DrRaw’s example, ask him to elaborate on how he arrived at his results.
Who knows, maybe this is a tutorial in the making!
@gadolf It’s really fast. I export the HDRmerge raw with a neutral tone curve into a 32bit float format. I then open this in a photo editor and duplicate into 2 layers for shadow and highlights. I apply the S curve for highlights ignoring the effect on shadows and blend it into the highlights region using blend if. Then I do the same for shadows. Ideally you try to get the contrast about equal across the board and then you can do one last S curve for everything.
I did in fact finish off with a Tonal Contrast effect from the NIK Collection, which is free, but honestly it’s kinda like icing on the cake.
But with that I loose all compressed dynamic range provided by enfuse. In the workflow I’m trying to achieve, I create images with different exposures from the hdrmerge output and then merge them with enfuse. With that, you compress all dynamic range into a single image, which could then be edited, revealing tonalities at taste. Also, by doing those steps on a wider gamut color space, you make sure you don’t loose any data. See this post.
Working with enfuse gives me much better results on the shadows:
My point is also achieving the same results on the highlights, which I thought I would be able to do in the same edit session. But, as @afre said, I probably will need to split this workflow into three parts, one for shadows, one for highlights and then merge the two outputs.
The result is quite flat, particularly in the sky…
Recently I have started to play with another method, which is based on the bilateral filter. This method is not new, and there is quite a lot of scientific literature on the subject (see for example this and this articles). It boils down to performing a two-level decomposition of the image, where a blurred version of the image is subtracted to the original one to isolate the high-frequency details. The contrast of the blurred image is then flattened to compress the overall dynamic range, and finally the high-frequency level is added back to restore the local details.
The key is in the blur operator: when using a simple gaussian kernel, the result will show visible halos around strong edges. This problem can be mitigated, or even practically removed, by using an edge-aware blur operator like the bilateral filter. Such blur operators are able to “distinguish” between fine-grained texture (that gets blurred) from hard edges (that are left unchanged). As a result, the high-frequency level will contain the fine-grained details, but not the hard edges, which are kept in the blurred version.
Here is what I could obtain with a simple application of the above method:
@Carmelo_DrRaw Thank you very much for taking your time and sharing your “new” workflow!
I loaded this image, applied your preset, and exported to a tif file. I did the same to other two images that produce a panorama.
Unfortunately, Hugin doesn’t seem to like these files: after setting up the parameters (finding the points / geometric and photometric optimization), when I click on the GL button (to start building the panorama), it crashes. I tried this for rec2000 tifs as well as for srgb’s. Reinstalled it but nothing.
When I have time I try to test this Hugin/Ubuntu 18.04 on other panoramas to see if the problem is with this new Ubuntu.
Thanks once more!
One can always edit the darkest photo alone. However, merging multiple exposures gives cleaner shadows with much reduced noise. While this might not be crucial in this specific case, it is at the basis of any HDR workflow (which is the initial topic of this thread).