One technique I have advocated in previous posts is the so-called Expose To The Right (ETRR) technique, which, because of the way digital tonal data is captured and stored, means that you should be seeking to push your exposure as far the right as possible, without ‘going over the edge’.
In this case, going over the edge means that some pixel sites become ‘full up’, ie no more photons can be captured and thus the electron count at that pixel site has maxed out. So how do you stop the sensor maxing out at places, but ensure an ETTR strategy?
There is a lot of information out there on the relative benefits of a full frame (large pixel) camera over a cropped DSLR or a small Point & Shoot camera. For those interested in learning more about the ‘science’ behind the camera, I commend this page: http://www.clarkvision.com/articles/does.pixel.size.matter/.
Yes, all the science is interesting; however, most of us have the camera we already own. So pixel size and sensor area are kind of irrelevant: we have what we have! Thus we can only maximize the quality of our captured data through using the ‘best’ in-camera workflow we can, eg using ETTR and, for very high dynamic range scenes, exposure bracketing.
In this post I offer the following two Magic Lantern enhanced strategies:
Strategy 1 covers a scene with ‘normal’ dynamic range, that is either fully contained within the sensor’s capture capability or has minimal clipping, ie at the shadow end. In this case I recommend adopting an ML Auto-ETTR-based workflow, ie:
- Enable Auto-ETTR in ML, ie enable the ETTR module and switch ETTR on;
- I prefer to use the SET button to generate an ETTR exposure, but some prefer a double-press of the shutter button;
- Set the ETTR parameters you need, ie clipping %, mid-range S/N override and or shadow S/N override;
- Compose and focus the scene, put the exposure on Manual and at 0Ev as a ‘first guess’;
- If you think the scene has a broader dynamic range than can be captured in one image, consider enabling Dual-ISO, eg a 100/800 shot (but note this requires more post processing, although this is pretty much automated now in Lightroom);
- Press SET (to generate the exposure time – note no image is taken);
- Press the shutter to capture the fully optimized ETTR image.
Strategy 2 covers a scene with a large dynamic range, ie even beyond that captured when using Dual-ISO ETTR processing, ie unacceptable clipping at both ‘ends’ of the histogram. In this case I recommend adopting an Auto-bracketing-based workflow, ie:
- Ensure Auto-ETTR and Dual-ISO are turned off in ML;
- Enable Auto-bracketing in ML and set the shot-2-shot Ev delta, eg 1 or 2 Ev is usually about right - remember the lower the Ev delta the more shots you will capture, and the higher the Ev delta the greater the possibility for generating post-processing artifacts;
- I prefer to initiate the auto-bracketing sequence from the shadow end. Thus what I would do is switch to LV and use the ML spot meter (set for Ev measurements) to ‘scan’ the scene in the areas where I wish to see shadow details and ensure this area is not clipped, eg place it in zone 3 or 4 (if you are exploiting the Zone System). If you use LV Exposure Simulation you can also get a visual clue and, of course, in ML LV you have Raw histograms, ie Canon’s are 8-bit JPEG-based ones. The LV scene will likely look blown out, but don’t panic!
- [An alternative auto-bracketing approach would be to simply put the exposure at 0Ev and let ML auto-bracketing ‘do its stuff’];
- Press the shutter to initiate the bracketing and the ML auto-bracketing algorithmics will do their magic; and because you started at the shadow end, ie no shadow clipping but with highlight clipping, you will end up with a bracket sequence that progressively brings the exposure down so that there is no highlight clipping;
- Post process in your favorite way, eg: PhotoMatix, HDR Efex-Pro or Photoshop etc.
Bottom line: for the Canon user Magic Lantern, with the right exposure workflow, guarantees you will never need worry about exposure. Thus you are free to think about the important things in an image, for example your artist vision.