Architecture-Aware Optimization Strategies in Real-time Image Processing

Architecture-Aware Optimization Strategies in Real-time Image Processing

Chao Li, Chinese Academy of Sciences, China
Souleymane Balla-Arabe, CNRS, France
Fan Yang, University of Burgundy, France


ISBN : 9781786300942

Publication Date : October 2017

Hardcover 180 pp

120.00 USD

Co-publisher

Description


In the field of image processing, many applications require real-time execution, particularly those in the domains of medicine, robotics and transmission, to name but a few.

Recent technological developments have allowed for the integration of more complex algorithms with large data volume into embedded systems, in turn producing a series of new sophisticated electronic architectures at affordable prices.

This book performs an in-depth survey on this topic. It is primarily written for those who are familiar with the basics of image processing and want to implement the target processing design using different electronic platforms for computing acceleration.

The authors present techniques and approaches, step by step, through illustrative examples. This book is also suitable for electronics/embedded systems engineers who want to consider image processing applications as sufficient imaging algorithm details are given to facilitate their understanding.

Contents


1. Introduction of Real-time Image Processing.
2. Hardware Architectures for Real-time Processing.
3. Rapid Prototyping of Parallel Reconfigurable Instruction Set Processor for Efficient Real-Time Image Processing.
4. Exploration of High-Level Synthesis Technique.
5. CDMS4HLS: A Novel Source- To-Source Compilation Strategy for HLS-Based FPGA Design.
6. Embedded Implementation of VHR Satellite Image Segmentation.
7. Real-time Image Processing with Very High-level Synthesis.

About the authors/editors


Chao Li works in Institute of Acoustics of Chinese Academy of Sciences. His research interests include image processing and acoustic detection.

Souleymane Balla-Arabe is a research fellow at LE2I CNRS-UMR laboratory. His research interests are GPU-based computations, computational intelligence, machine learning, and computer vision.

Fan Yang is Full Professor at University of Burgundy. Her current research focuses on eHealth, neural network, and real-time image processing.