How to measure visual salience quantitatively Salience makes objects pop-up from their surrounding and immediately attract our attention. A salient object in the visual domain would, e.g., be a red dot among white ones. We can sometimes intuitively say an object is more salient than the other, e.g., a moving red dot might be more salient than a static one. 

Is there a way to quantify how salient an object is?



UPDATE

To narrow down the question a little, suppose you have a set of different output devices that can provide either visual or auditory cues (LEDs, loudspeakers, lamps, screens...) and they are near a target object you which to attract attention to. Ideally one would choose the output device that is closest to the target object to attract attention, but depending on the distance, the output device may not be as conspicuous. So at a given distance, I would like to know, which device will attract attention the most. The environment would be mostly static and well lit.
The duration of eye fixation has been used in  both infants and adults to measure locus of attention. This can be achieved using an eye-tracker. A more primitive and less exact way is to manually count the frames of a video recording of subjects. The frames per second (FPS) would be a limiting factor. In addition, the item that was first observed is the more salient one, provided that there is no secondary bias in the task (i.e. the objects should be an equal distance apart or the distance could be randomized).

For visual search and serial search tasks, responses are gathered and individual response curves (reciever operator characteristics, ROC) for participants and conditions can be computed using signal detection theory (SDT). The discrimination index d prime (d') can then be calculated only if two explicit responses are required exist.

Another option is to vary the presentation time systematically in order to quantify processing speed, but this requires a more computational approach.