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 is 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.' But read more...
This research has been conducted in Jordan at the Department of Information Technology at Al-Balqa Applied University by Associate Professor Alaa Sheta and Malik Braik.
They've worked with Aladdin Ayesh, of the Centre for Computational Intelligence (CCI) at De Montfort University in Leicester,UK. For more information about Ayesh's works, here is a link to his personal website.
Now, let's see how PSO can be applied to photo processing. "PSO is based on a mathematical model of the social interactions of swarms. The algorithm treats each version of an image as an individual member of the swarm and makes a single, small adjustment to contrast levels, edge sharpness, and other image parameters. The algorithm then determines whether the new members of the swarm are better or worse than the original according to an objective fitness criterion."
And here are more explanations. "'The objective of the algorithm is to maximize the total number of pixels in the edges, thus being able to visualize more details in the images,' explain the researchers. Such enhancement might be useful in improving snapshots of CCTV quality for identification of individuals or vehicle number plates, it might also have application in improving images produced with lower quality cameras, such as camera phones, that are required for use in publishing or TV where image quality standards are usually higher. The process of enhancing step by step is repeated to create a swarm of images in computer memory which have been 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."
This research work has been included in a recent issue of Inderscience's International Journal of Innovative Computing and Applications (IJICA) under the title "Particle swarm optimisation enhancement approach for improving image quality" (Volume 1, Issue 2, Pages 138-145, 2007).
Here is an excerpt from the abstract describing how the pictures are optimized. "The enhancement process is a non-linear optimisation problem with several constraints. Based upon a mathematical model of the social interactions of swarms, the algorithm has been shown to be effective at finding good solutions of the enhancement problem by adapting the parameters of a novel extension to a local enhancement technique similar to statistical scaling. This enhances the contrast and detail in the image according to an objective fitness criterion. The proposed algorithm has been compared with Genetic Algorithms (GAs) to a number of tested images. The obtained results using grey scale images indicate that PSO is better than GAs in terms of the computational time and both the objective evaluation and maximisation of the number of pixels in the edges of the tested images."
For more information about PSO, here is a link to this Wikipedia page.
Is this idea worth it? Maybe yes. But first, I haven't found on the Web any pictures enhanced by this algorithm. And second, even the researchers don't say if this project will hace future commercial applications.
Sources: Inderscience Publishers news release, February 1, 2008; and various websites
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