IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Special Section on VLSI Design and CAD Algorithms
Framework and VLSI Architecture of Measurement-Domain Intra Prediction for Compressively Sensed Visual Contents
Jianbin ZHOUDajiang ZHOULi GUOTakeshi YOSHIMURASatoshi GOTO
Author information
JOURNAL RESTRICTED ACCESS

2017 Volume E100.A Issue 12 Pages 2869-2877

Details
Abstract

This paper presents a measurement-domain intra prediction coding framework that is compatible with compressive sensing (CS)-based image sensors. In this framework, we propose a low-complexity intra prediction algorithm that can be directly applied to measurements captured by the image sensor. We proposed a structural random 0/1 measurement matrix, embedding the block boundary information that can be extracted from the measurements for intra prediction. Furthermore, a low-cost Very Large Scale Integration (VLSI) architecture is implemented for the proposed framework, by substituting the matrix multiplication with shared adders and shifters. The experimental results show that our proposed framework can compress the measurements and increase coding efficiency, with 34.9% BD-rate reduction compared to the direct output of CS-based sensors. The VLSI architecture of the proposed framework is 9.1 Kin area, and achieves the 83% reduction in size of memory bandwidth and storage for the line buffer. This could significantly reduce both the energy consumption and bandwidth in communication of wireless camera systems, which are expected to be massively deployed in the Internet of Things (IoT) era.

Content from these authors
© 2017 The Institute of Electronics, Information and Communication Engineers
Previous article Next article
feedback
Top