High dynamic range

High dynamic range (HDR) is used to refer to photographs which have captured a broader range of luminosity values than what is usual. In most contexts it implies a higher dynamic range than a digital camera sensor can detect between saturation and its noise floor. How can this be achieved? By combining several images so that different parts of the scene come for images taken with different exposure settings. In other words exposure bracketing followed by digital processing to merge the images. If you do not know what is the meaning of bracketing in photography please first read my earlier post on the subject.

If one captures raw images instead of compressed JPEG images, one can in post-processing increase to a significant extent the dynamic range by adjusting the tone curve. In many cases this is enough. However, when the luminosity range in a scene is extreme, the method described here can be the best approach.

Example on a cloudy day, merging of three bracketed images or adjustment of the tone curve in the image exposed optimally, do not differ by much.

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HDR techniques based on merging of images can be used only with static subjects or slowly moving ones. How much is slowly enough depends on how fast the sequence is obtained, and on whether the moving object crosses a boundary between well and poorly illuminated areas; i.e. would cross the boundary between images that are combined. In the example below the cyclist was moving rather fast, but within the dark part of the image.

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Some modern digital cameras, can even do the merging in real-time, generating a merged JPEG file.

Merging and processing of the images can be tricky in that if the dynamic range achieved is very broad, images look unnatural. Used with moderation, it is a useful tool for pictorial photography. In scientific and documentary imaging, it can be very useful, as it can ensure that exactly the same camera settings and image processing settings can be used across pictures of subjects with different luminosity, avoiding possible bias.


As instead of trying to “nail” the perfect exposure as when bracketing exposure settings with the intention keeping a single best exposed picture, we are trying to extend the dynamic range by combining images, so bracketing is best done in relatively large steps of from 2 EV to 3 EV as in the examples above.

The merging of the images can be done using different software, with different degrees of automation vs. manual control. In most cases imperfect alignment of the images is automatically corrected, and in many cases small movements of subjects are automatically identified and “masked”. Lightroom does a quite good job in many cases and with little user intervention. However, it does not allow manual retouching or manual setting of masks, which can be needed in some cases. The merged images in this post were created and edited in Lightroom CC 6.13.

HDR techniques can be useful all the way from landscape photography to macrophotogarphy.

Another technique based on merging several images is focus stacking, which I described in an earlier post.

All illustrations, and text are of my own authorship, and copyrighted.

(c) 2017 Pedro J. Aphalo


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