Back in time when I was at university, my very first DSP lectures were actually not about audio but image processing. Due to my interest in photography I followed this amazing and ever evolving domain over time. Later on, High Dynamic Range (HDR) image processing emerged and beside its high impact on digital photography, I immediately started to ask myself how such techniques could be translated into the audio domain. And to be honest, for quite some time I haven’t got a clue.
This image shows a typical problem digital photography still suffers from: The highlights are completely washed out and so the lowlights are turning into black abruptly w/o containing further nuances – the dynamic range performance is pretty much poor and this is actually not what the human eye would perceive since it features both: a higher dynamic range per se but also a better adoption to different (and maybe difficult) lighting conditions.
On top, we have to expect severe dynamic range limitations in the output entities whether that’s a cheap digital print, a crappy TFT display or the limited JPG file format, just as an example. Analog film and prints does have such problems in principle also but not to that much extend since they typically offer more dynamic resolution and the saturation behavior is rather soft unlike the digital hard clipping. And this is where HDR image processing chimes in.
It typically distinguishes between single- and multi-image processing. Within multi-image processing, a series of Low Dynamic Range (LDR) images are taken in different exposures and combined into one single new image which contains an extended dynamic range (thanks to some clever processing). Afterwards, this version is rendered back into an LDR image by utilizing special “tone mapping” operators which are performing a sort of dynamic range compression to obtain a better dynamic range impression but now in a LDR file.
Within single-image processing, there must be one single HDR image already available and then just tone mapping is applied. As an example, the picture below takes advantage of single-image processing from a RAW file which typically does have much higher bit-depth (12 or even 14 bit as of todays sensor tech) opposed to JPG (8 bit). As a result a lot of dynamic information can be preserved even if the output file still is just a JPG. As an added sugar, such a processed image also translates way better over a wide variety of different output devices, displays and viewing light conditions.