Orasis is a Biologically-Inspired Image Processing software, developed by Vassilios Vonikakis and is partially based on his PhD research. The main objective of Orasis is to make photographs look closer to the human perception of the scene, by compensating for High-Dynamic Range conditions, color casts, reduced local contrast and noise. This software was formerly named "PhotoEnhancer", but the name was dropped due to copyright issues.
Orasis can enhance your images in the following 4 ways:
1. Enhancement of the under/overexposed image regions, without affecting the correctly exposed ones. Many times the image captured by a camera and the image in our eyes are dramatically different. Especially when there are shadows or highlights in the same scene. In these cases our eyes can distinguish many details in the shadows or the highlights, while the image captured by the camera suffers from loss of visual information in these regions. Orasis employs characteristics of the ganglion cells of the Human Visual System, exhibiting improved local equalization of brightness and contrast.
2. Enhancement of the local contrast. The transmittance of a scene plays a very important role to the overall quality of the image. Smoke, fog or the atmosphere, can decrease the local contrast of images, e.g. aerial photos, photos with extended use of zoom etc. Orasis employs biologically inspired algorithms which compensate for this phenomenon and improve the overall clarity of the image.
3. Color correction. The Human Visual System exhibits some degree of color constancy. This means that the perception of colors is not affected considerably by the presence of unknown light sources in a scene. On the other hand, cameras are affected much more by the color of the scene’s light. Unless a proper white balance setting is selected, images taken under incandescence light will look yellowish or images taken in the sunset will look reddish etc. Orasis employs many algorithms which correct the overall colors of the scene, by removing automatically color casts. Among them, there are also local color correction algorithms, which can compensate for the effects of many light sources in the scene.
4. Noise reduction. Enhancing underexposed image regions, will inevitably result to noise appearance in these areas. Trying to reduce this noise, will affect the whole image, deteriorating the overall appearance. Until now, the only way to deal with this was a manual application of denoising filters to these specific image regions, something which is quite time consuming. Orasis employs noise reduction algorithms which affect only the underexposed image regions, leaving intact the correctly exposed ones. With the press of a button, the noise in the underexposed image regions will be removed without affecting other parts of the image.
Aiming in the above four directions, Orasis attempts to bridge the gap between "what you see" and "what the camera sees". The final result is a lot closer to the human perception of the scene, than the original captured image, revealing visual information that otherwise wouldn't be available to the human observer.