Particle Swarm Optimization for Picture Analysis

Roland Piquepaille writes "Particle swarm optimization (PSO) is a computer algorithm based on a mathematical model of the social interactions of swarms which was first described in 1995. Now, researchers in the UK and Jordan have carried this swarm approach to photography to 'intelligently boost contrast and detail in an image without distorting the underlying features.' This looks like a clever concept even if I haven't seen any results. The researchers have developed an iterative process where a swarm of images are created by a computer. These images are 'graded relative to each other, the fittest end up at the front of the swarm until a single individual that is the most effectively enhanced.'"

Re:Wow

[Smordnys s'regrepsA]

Let me just point out your sig

Careful What You Wish For..

So, did you realize an optimized goatse fits your wish for a picture of "something...anything"?

yeah...

[cosmocain]

This looks like a clever concept even if I haven't seen any results.

Hell, this needs no comment, it's funny on its own. Mod TFB +1, accidently funny.

Re:The only problem...

[somersault]

Yep because it makes lots of financial sense to have a few supercomputers plugged into your TV so that you can get your contrast setup correctly..

Re:Optimization algorithm

[CmdrGravy]

A first pass analysis certainly reveals some elements of Metropolis-Hastings may have been folded in but they do not comprise the entirety of the final solution which seems instead to be bulked up by a n'th pass reverse locality filter feeding off a more traditionally schwelpian treatment of the core triplets. Interestingly every fifth haynes cosignatory node seems to be commulated back to it's quatenary closest fit counterpart.