How does Orasis compare against other popular photography apps:

Generally, it is very different to evaluate the results of applications which enhance images. We decided however to conduct a more scientific comparison by essentially subtracting the pixel values between the original and the enhanced image.
In the end result:

  • dark blue regions indicate very small differences with the original image,
  • cyan-yellow regions indicate substantial differences and
  • red-orange regions indicate very strong differences between the original image and the application’s result.

Please refer to the chromatic legend below for your benefit. It resembles temperature maps used in weather forecasts, where blue indicates low temperatures (low pixel differences), and red indicates high temperatures (high pixel differences). Consequently, a “theoretically perfect” enhancement algorithm would exhibit cyan, yellow, or even red colors in the regions of the original image which require extensive correction. On the other hand, it would exhibit only a dark blue color for the regions of the original image which do not require any correction.

 

 

Please see below how does Orasis compare with some significant applications from our competition (for obvious reasons we cannot reveal names):



Application #1 exhibits 2 major problems:

  1. It affects the normal regions (significant part of the normal regions are light blue – they are incorrectly lighten)
  2. There is not enough enhancement in the dark areas (the man’s body is dark blue - not enhanced adequately)


Application #2 exhibits one of the most common problems, which is found in many existing applications:

  1. It affects significantly the normal regions, which is a result of its non-local enhancement algorithm (the background is cyan - it is incorrectly lighten). As a result, there is loss of local contrast in the correct regions, which tend to look washed-out.  
  2. The dark areas are not improved evenly (the man’s body is dark blue in one part and light blue in the other part)


Application #3 exhibits another common problem:

  1. Halo artifacts: a white unnatural band which appears in the boundaries between dark and bright regions.
  2. It affects significantly some of the normal regions, while it leaves intact others.


Contrary to the above competitive applications, Orasis exhibits the unique following characteristics, which derive from its brain-inspired algorithm:

  1. It significantly and evenly enhances the dark image regions (the man’s body is cyan). The enhancement is greater than any of the above applications.
  2. It does not affect the normal regions (all normal regions are dark blue - minimal difference with original image). None of the above applications preserves in such degree the normal regions.
  3. It does not exhibit halo artifacts in the boundaries between the dark and the bright image regions.