CHENNAI - A new software designed by two Indian electronic engineers gleans clear pictures out of hazy or blurry images.

S.Uma, from the Coimbatore Institute of Technology, and S. Annadurai from the Government College of Technology, Coimbatore, have turned to neural networks to help them clean up their image.

Uma and Annadurai have developed a modified network that builds and extends the work of others to allow them to quickly process an image reducing distortion, noise and blurring.

An analysis of the before and after shows that quality is improved by between 39 percent and 67 percent using the team's approach and results take half the time compared to other methods.

The approach could significantly reduce information loss while reversing blurring caused by lens aberrations and faults, and could reduce noise that distorts the appearance of an image.

The team suggests that distortions in an image due to atmospheric disturbances between camera and distant subjects could be unravelled and a photo taken on a hot, hazy day made acceptable.

The researchers point out that earlier attempts at this kind of inverse filtering of an image relied on the image having a high signal-to-noise (SNR) ratio.

Other approaches require huge amounts of computing power and are generally untenable. This is especially true in the fledgling field of artificial vision, whether robotic or prosthetic. However, some success with neural networks has been achieved.

Errant pixels and blurry regions in a photo, whether digital or scanned, are the bane of lensmen, worldwide.

Moreover, in vision processing research, degraded photos are common and require restoration to a high-quality un-degraded state.

These findings have been published in the International Journal of Signal and Imaging Systems Engineering.