Hardware Acceleration of a Neighborhood Dependent Component Feature Learning (NDCFL) Super-Resolution Algorithm

Image processing and computer vision algorithms allow computers to make sense of pictures and video seen through cameras. These have applications in a large variety of “real time” applications like surveillance, intelligence gathering, robotics, automobile driving, aviation, etc., where the picture from the video needs to be processed by a computer as soon as it is taken. However these algorithms are time intensive because of its compute bound nature. In this literature, a single image super resolution algorithm based on Neighborhood Dependent Component Feature Learning (NDCFL) is accelerated by multiple GPUs and multiple CPU cores, using NVIDIA’s Computer Unified Device Architecture (CUDA), OpenCV and POSIX threads. Given a low resolution input, this method uses image features to adaptively learn the regression kernel based on local covariance to estimate the high resolution image. The accelerated implementation performs at speed 51 times faster than that of original implementation for 590X580 frame, and achieves processing rate close to real-time.

Name thesis:degree_name

Master of Science (M.S.)

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Electrical Engineering

Grantor dc:publisher

University of Dayton

Year dc:date

2013

Author dc:creator

• Mathari Bakthavatsalam, Pagalavan

Contributors dc:contributor

• Taha, Tarek

• Electrical Engineering
• Computer Engineering
• Engineering
• GPU
• CUDA
• GPGPU
• Super-resolution on GPU
• Acceleration of super-resolution
• Image Processing
• NDCFL
• super-resolution
• GPU acceleration
• Accelerating Image processing algorithm using GPU
• Multi-core acceleration

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=dayton1366034621

OAI identifier oai:identifier

oai:etd.ohiolink.edu:dayton1366034621