This paper presents a system for real-time video reception in low-power mobile devices using Digital Audio Broadcast (DAB) technology for transmission. A demo receiver terminal is designed into a FPGA platform using the Advanced Simple Profile (ASP) MPEG-4 standard for video decoding. In order to keep the demanding DAB requirements, the bandwidth of the encoded sequence must be drastically reduced. In this sense, prior to the MPEG-4 coding stage, a pre-processing stage is performed. It is firstly composed by a segmentation phase according to motion and texture based on the Principal Component Analysis (PCA) of the input video sequence, and secondly by a down-sampling phase, which depends on the segmentation results. As a result of the segmentation task, a set of texture and motion maps are obtained. These motion and texture maps are also included into the bit-stream as user data side-information and are therefore known to the receiver. For all bit-rates, the whole encoder/decoder system proposed in this paper exhibits higher image visual quality than the alternative encoding/decoding method, assuming equal image sizes. A complete analysis of both techniques has also been performed to provide the optimum motion and texture maps for the global system, which has been finally validated for a variety of video sequences. Additionally, an optimal HW/SW partition for the MPEG-4 decoder has been studied and implemented over a Programmable Logic Device with an embedded ARM9 processor. Simulation results show that a throughput of 15 QCIF frames per second can be achieved with low area and low power implementation.
[1]
Wen-Hsiao Peng,et al.
A Software-Hardware Co-Implementation of MPEG-4 Advanced Video Coding (AVC) Decoder with Block Level Pipelining
,
2005,
J. VLSI Signal Process..
[2]
Daniel Gross,et al.
Improved resolution from subpixel shifted pictures
,
1992,
CVGIP Graph. Model. Image Process..
[3]
Peter Pirsch,et al.
Multicore system-on-chip architecture for MPEG-4 streaming video
,
2002,
IEEE Trans. Circuits Syst. Video Technol..
[4]
P ? ? ? ? ? ? ? % ? ? ? ?
,
1991
.
[5]
Luis Alvarez,et al.
Motion Estimation Techniques in Super-Resolution Image Reconstruction. A Performance Evaluation
,
2006
.
[6]
Pedro P. Carballo,et al.
CASSE: a system-level modeling and design-space exploration tool for multiprocessor systems-on-chip
,
2004
.
[7]
Aggelos K. Katsaggelos,et al.
Region-based super-resolution for compression
,
2007,
Multidimens. Syst. Signal Process..