Signal Processing Commons^™

Parallel Computation In Communication And Signal Processing, Amean Al_Safi, Bradley Bazuin, Liqaa Alhafadhi

Amean S Al_Safi

The powerful computation of GPU has increased the computation speed up of many systems. This paper summarize some of the most important work in the field of communication and signal processing using GPU

Adaptive Motion Pooling And Diffusion For Optical Flow, Naga Venkata Kartheek Medathati, Pierre Kornprobst, Guillaume Masson, Manuela Chessa, Fabio Solari

MODVIS Workshop

We study the impact of local context of an image (contrast and 2D structure) on spatial motion integration by MT neurons. To do so, we revisited the seminal work by Heeger and Simoncelli (HS) [4] using spatio-temporal filters to estimate optical flow from V1-MT feedforward interactions. However, the HS model has difficulties to deal with several problems encountered in real scenes (e.g., blank wall problem and motion discontinuities). Here, we propose to extend the HS model with adaptive processing by focussing on the role of local context indicative of the local velocity estimates reliability. We set a network structure representative …

Optimizing Harris Corner Detection On Gpgpus Using Cuda, Justin Loundagin

Master's Theses

ABSTRACT

Optimizing Harris Corner Detection on GPGPUs Using CUDA

The objective of this thesis is to optimize the Harris corner detection algorithm implementation on NVIDIA GPGPUs using the CUDA software platform and measure the performance benefit. The Harris corner detection algorithm—developed by C. Harris and M. Stephens—discovers well defined corner points within an image. The corner detection implementation has been proven to be computationally intensive, thus realtime performance is difficult with a sequential software implementation. This thesis decomposes the Harris corner detection algorithm into a set of parallel stages, each of which are implemented and optimized on the CUDA platform. …