HDR: Automated Local Dynamic Range Optimization

Top Left: Source. Top Right: 'Tame' algorithm taming the bright core. Bottom Left: 'Equalize' algorithm taming bright core and lifting detail in shadows for a uniformly lit image. Bottom Right: 'Reveal' algorithm recovering dark structures within low dynamic range areas.

The HDR module optimises local dynamic range, in order to bring the maximum amount of detail that is hidden in your data.

A HDR optimisation tool is a virtual necessity in astrophotography, owing to the huge brightness differences of the objects that exist in space.

As opposed to other approaches (for example wavelet-based ones), StarTools' HDR enhances dynamic range allocation locally (not just globally) and takes into account psycho-visual theory (i.e. the way human vision perceives and processes detail). The result is an artefact free, totally natural looking image with real detail that does not suffer from the problems that other approaches suffer from, such as looking 'flat', looking too busy, or blowing out highlights such as stars.

3 subtly different algorithms are available to address 4 different common dynamic range challenges;

  1. The 'Equalize' algorithm lifts faint detail and tames distracting glare and bright cores.
  2. The 'Optimize' algorithm uses dynamic range manipulation to enhance psycho-visual acuity without modifying actual detail.
  3. The 'Reveal' algorithm digs deep into bright DSO cores, extracts any detail it can find and re-embeds the detail in a corrected (less bright) super structure.

The results are absolutely impeccable and you'll be wondering why you were ever bothering with confusing and sub-optimal wavelet layers, or blunt tools like global shadow, midtone, highlight manipulation.


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