Now, a new approach to improve photosFebruary 3rd, 2008 - 5:42 pm ICT by admin
Washington, Feb 3 (ANI): Researchers in the UK and Jordan have developed a new approach to clean up digital photos and other images.
The researchers have revealed that their new technique to improve photos is based on a population-based evolutionary computer algorithm, known as Particle Swarm Optimization (PSO).
A study has revealed that PSO may help boost contrast and detail in an image without distorting the underlying features, they say.
The scientists say that the PSO algorithm represents an entirely new approach to solving all kinds of optimisation problems.
The PSO algorithm a kind of swarm intelligence that is based on social-psychological principles and provides insights into social behaviour, as well as contributing to engineering applications.
According to the researchers, the algorithm treats an images each version as an individual member of the swarm and makes a single, small adjustment to contrast levels, edge sharpness, and other image parameters.
It, then, determines whether the new members of the swarm are better or worse than the original according to an objective fitness criterion.
“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,” the researchers said.
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.
“The obtained results using grey scale images indicate that PSO is better than other approaches in terms of the computational time and both the objective evaluation and maximization of the number of pixels in the edges of the tested images,” the researchers said.
The study is published in Inderscience’s International Journal of Innovative Computing and Applications. (ANI)
Tags: computational time, computer algorithm, computer memory, contrast levels, digital photos, edge sharpness, fitness criterion, grey scale images, image parameters, innovative computing, insights, jordan, new approach, objective evaluation, optimisation problems, particle swarm optimization, scientists, social behaviour, social psychological principles, swarm intelligence