October 2013 Embedded Vision Summit Technical Presentation: “Efficient Super-Resolution Algorithms and Implementation Techniques for Constrained Applications,” Ilan Yona, CEVA

Ilan Yona, Director of Imaging and Computer Vision at CEVA, presents the "Efficient Super-Resolution Algorithms and Implementation Techniques for Constrained Applications" tutorial within the "Front-End Image Processing for Vision Applications" technical session at the October 2013 Embedded Vision Summit East.

Image quality is a critical challenge in many applications, including smart phones, especially when using low quality sensors or when using digital zoom for enlarging part of the image. Super-resolution is a set of techniques that can address this challenge by combining multiple images to produce a single, higher quality image. However, super-resolution can be extremely computationally demanding, so when implementing it on a constrained platform (such as a smart phone), the algorithm should be carefully chosen, balancing image quality, speed, and power consumption.

CEVA tested variety of known super-resolution algorithms and found that they were not efficient for cost- and power-constrained systems. The company then developed a new algorithm that produces good quality images and is suitable for constrained systems. In this talk, Ilan Yona explains how super-resolution works, introduces the previously known algorithms, and presents CEVA's new algorithm and a sample implementation of it.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



1646 N. California Blvd.,
Suite 360
Walnut Creek, CA 94596 USA

Phone: +1 (925) 954-1411
Scroll to Top