We’ve all been there. The subject of the picture is in the shade but the background is brightly lit. What do we do? Expose for the subject and accept that the background will be overexposed and washed out? Or do we make sure the background is right and hope that we can lift the shadow lighting sufficiently in post-processing to recover the detail of the subject? Sometimes this works but in extreme cases, as in the example below, it will not.
So what else can we do?
HDR has to be worth a try. However even that may fail if the dreaded HDR “ghosts” put in an appearance. Ghosts are caused by the independent movement of some picture elements between exposures. For example leaves moving in the wind may show up in multiple positions in the final image. HDR software is improving all the time and the better packages have become quite good at reducing ghosts, but there are situations where they will not be entirely successful and you will be left looking for another way to obtain a satisfactory image.
So is there is another way? Yes, if you are using a reasonably modern camera with a low noise CMOS sensor (DLSR and mirror-less cameras sold during the last few years) and you are prepared to save your image in a raw format, use a bit depth of at least 12 and preferably 14 and use a low ISO (200 or less). The rest of this article explains how to do it.
From one raw file, shot with critical exposure accuracy, you can construct a set of bracketed files suitable for HDR processing. Because all of these files will be sourced from a single raw file there can be no ghosting.
A critically accurate exposed (optimal) raw file is one that overexposed by 1 EV in order to give you the best chance of detail recovery in the shadows, while still being able to recover the blown highlights. Generally you can consistently recover around one stop of overexposure from a raw file. Any more than that and the information in the burned out area is lost for all time. The trick is to get an image file which is right on the edge of having unrecoverable blown highlights. This is often referred to as shooting to the right (of the histogram). To be sure to get a suitable exposure it is essential to do an exposure bracket – you can do this manually if your camera doesn’t provide automatic bracketing.
When you shoot the picture I suggest you bracket your exposure by +/- 1 EV. Check your blinking highlight display and/or histogram and see if you have a workable file. If not and the situation allows then offset your EV by 3 and try another +/- 1 EV bracket sequence. Of course if you have a camera that can take 5 or more bracketed images then just take as many shots as seems sensible. I would suggest at least 5, say -2 EV through to +2EV in 1EV steps. But get an even wider range if you can. Achieving accurate exposure in these conditions is often tricky in itself, so the wider the bracket range the better the chance of obtaining an optimal image. What you have done at this stage is to have created a set of image files that should include one file which is close enough to the optimal image to start the post-processing. You can single out this file once you have downloaded the files to your computer.
To identify the most suitable image use a raw converter, such as the Adobe Camera Raw package that comes as part of Lightroom, PhotoShop or Elements. Determine which file is over exposed between 0EV and 1EV. You should check not only the luminance for over-exposure but also each of the three colour channels, because overexposure in even one channel may cause significant colour shift in the overexposed area.
Save a copy as a 16 bit TIF file or a maximum quality 8 bit JPEG. In general TIF files are preferred over JPEG because of the additional bit depth and lack of compression, however for this purpose I find a maximum quality JPEG is satisfactory because each file only needs to hold a portion of the overall dynamic range of the final image. Now successively adjust the exposure slider to -1EV (to recover the highlights) then to +1 EV, +2 EV and finally +3 EV. For each EV setting save the output of your converter in the same file format as your first save. Make sure you provide a different name for each file.
Now you should carefully apply noise reduction to the two brightest images. The other images should not need it. You will need a good noise reduction program or plug-in. I currently use Topaz DeNoise 5 as a plug-in with Elements 11 – no you do not need the latest version of Element’s pricy sibling for this task. But good quality noise reduction software is essential. If you shot at 200 ISO your brightest file may be the equivalent of 1600 ISO in terms of its noise performance and for that file you will certainly need to reduce the noise while maintaining sufficient detail. Generally the noise reduction provided in the all-purpose post-processing software tends not to be up to it for this very demanding task.
Next blend the five output images using an HDR package. I use PhotomatixPro but any reputable HDR software should be satisfactory. With any HDR software you should master it before you take on this task. At this
stage we are putting the recipe book aside and working from touch and feel. You just have to tweak and learn, but once you ”know” your software and how to make it work for your style it becomes a straight forward process.
When you have produced the HDR image it is quite normal for it to require both global and local adjustments to contrast, brightness and saturation. The HDR software has had to make some arbitrary decisions in order to fit such a wide range of luminance into the limited luminance range that can be displayed by your monitor or print and you will need to adjust the image to however you feel it should look.
Along than the initial choice and positioning of the subject, this is the creative part of the exercise. I think of this as the “painterly” stage. In terms of software I have found that Nikon Capture NX2 is particularly effective for this purpose. It is very easy to use and very fast at localised editing, but you may find other packages also effective. What is most important is that you understand and are comfortable using all of the necessary tools in whichever software you use. Again there is no recipe at this stage, you just need to know which tools you have and when and how to use them. This will come with practice.
This process may sound quite daunting and appear to involve lot of effort. Yes it may be daunting, but surely that is one reason why you belong to a photography club. We are here to help each other and for every question you ask there will someone able to help you find an answer. In terms of effort, from downloading the camera to producing an image like the one above typically takes me 15 to 30 minutes.
If we are prepared to take control of modern cameras and processing software then in respect of handling dynamic range they are awesome. So if you haven’t already done so start now to make the most of this amazing technology. Shrug off the dark and turn on the light.
High-dynamic-range imaging (or HDR) is a set of techniques used in imaging and photography to reproduce a greater dynamic range of luminosity than possible using standard digital imaging or photographic techniques. HDR images can represent more accurately the range of intensity levels found in real scenes, from direct sunlight to faint starlight, and is often captured by way of a plurality of differently exposed pictures of the same subject matter. Standard (Non-HDR) cameras take photographs with a limited exposure range (around 3eV), resulting in the loss of detail in bright or dark areas. The eye will perceive tones over a range of around 11eV. HDR compensates for this loss of detail by capturing multiple photographs at different exposure levels and combining them to produce a photograph representative of a broader tonal range. The two primary types of HDR images are computer renderings and merged images. Images can be merged from multiple low -dynamic-range (LDR)[5] or standard-dynamic -range (SDR)[6] photographs. HDR images can also be acquired using special image sensors, like oversampled binary image sensor. Tone mapping methods, which reduce overall contrast to facilitate display of HDR images on devices with lower dynamic range, can be applied to produce images with preserved or exaggerated local contrast for artistic effect.
Source—Wikipaedia
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