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Mobile Audiovisual Terminal: System Design and Subjective Testing in DECT and UMTS networks
It is anticipated that there will shortly be a requirement
for multimedia terminals that operate via mobile
communications systems. This paper presents a functional specification
for such a terminal operating at 32 kb/s in a digital
European cordless telecommunications (DECT) and universal
mobile telecommunications system (UMTS) radio network. A terminal
has been built, based on a PC with digital signal processor
(DSP) boards for audio and video coding and decoding. Speech
coding is by a phonetically driven code-excited linear prediction
(CELP) speech coder and video coding by a block-oriented hybrid
discrete cosine transform (DCT) coder. Separate channel coding
is provided for the audio and video data. The paper describes the
techniques used for audio and video coding, channel coding, and
synchronization. Methods of subjective testing in a DECT network
and in a UMTS network are also described. These consisted of
subjective tests of first impressions of the mobile audio–visual
terminal (MAVT) quality, interactive tests, and the completion
of an exit questionnaire. The test results showed that the quality
of the audio was sufficiently good for comprehension and the
video was sufficiently good for following and repeating simple
mechanical tasks. However, the quality of the MAVT was not
good enough for general use where high-quality audio and video
was needed, especially when transmission was in a noisy radio
environment
Full Reference Objective Quality Assessment for Reconstructed Background Images
With an increased interest in applications that require a clean background
image, such as video surveillance, object tracking, street view imaging and
location-based services on web-based maps, multiple algorithms have been
developed to reconstruct a background image from cluttered scenes.
Traditionally, statistical measures and existing image quality techniques have
been applied for evaluating the quality of the reconstructed background images.
Though these quality assessment methods have been widely used in the past,
their performance in evaluating the perceived quality of the reconstructed
background image has not been verified. In this work, we discuss the
shortcomings in existing metrics and propose a full reference Reconstructed
Background image Quality Index (RBQI) that combines color and structural
information at multiple scales using a probability summation model to predict
the perceived quality in the reconstructed background image given a reference
image. To compare the performance of the proposed quality index with existing
image quality assessment measures, we construct two different datasets
consisting of reconstructed background images and corresponding subjective
scores. The quality assessment measures are evaluated by correlating their
objective scores with human subjective ratings. The correlation results show
that the proposed RBQI outperforms all the existing approaches. Additionally,
the constructed datasets and the corresponding subjective scores provide a
benchmark to evaluate the performance of future metrics that are developed to
evaluate the perceived quality of reconstructed background images.Comment: Associated source code: https://github.com/ashrotre/RBQI, Associated
Database:
https://drive.google.com/drive/folders/1bg8YRPIBcxpKIF9BIPisULPBPcA5x-Bk?usp=sharing
(Email for permissions at: ashrotreasuedu
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