| Paper: | IMDSP-P9.10 | ||
| Session: | Filtering, Interpolation and Superresolution | ||
| Time: | Wednesday, May 17, 16:30 - 18:30 | ||
| Presentation: | Poster | ||
| Topic: | Image and Multidimensional Signal Processing: Image Filtering | ||
| Title: | Basis Projection for Linear Transform Approximation in Real-Time Applications | ||
| Authors: | Yinpeng Chen, Hari Sundaram, Arizona State University, United States | ||
| Abstract: | This paper aims to develop a novel framework to systematically trade-off computational complexity with output distortion, in linear multimedia transforms, in an optimal manner. The problem is important in real-time systems where the computational resources available are time-dependent. We solve the real-time adaptation problem by developing an approximate transform framework. There are three key contributions of this paper – (a) a fast basis approximation framework that allows us to store signal independent partial transform results to be used in real-time, (b) estimating the complexity distortion curve for the linear transform using a basis set and (c) determining optimal operating points and a meta-data embedding algorithm for images that allows for real-time adaptation. We have applied this approach on the FFT transform with excellent results. | ||
©2018 Conference Management Services, Inc. -||- email: webmaster@icassp2006.org -||- Last updated Friday, August 17, 2012