(IJACSA) International Journal of Advanced Computer Science and Applications,
Vol. 7, No. 4, 2016
167 | P a g e
www.ijacsa.thesai.org
Novel Approach to Estimate Missing Data Using
Spatio-Temporal Estimation Method
Aniruddha D. Shelotkar
Research Scholar,
Department of Electronics Engineering
SGB Amravati University, Amravati
Maharashtra, India
Dr. P. V. Ingole
Principal,
G. H. Raisoni Institute of Engineering
and Management, Amravati
Maharashtra, India
Abstract—With advancement of wireless technology and the
processing power in mobile devices, every handheld device
supports numerous video streaming applications. Generally, user
datagram protocol (UDP) is used in video transmission
technology which does not provide assured quality of service
(QoS). Therefore, there is need for video post processing modules
for error concealments. In this paper we propose one such
algorithm to recover multiple lost blocks of data in video. The
proposed algorithm is based on a combination of wavelet
transform and spatio-temporal data estimation. We decomposed
the frame with lost blocks using wavelet transform in low and
high frequency bands. Then the approximate information (low
frequency) of missing block is estimated using spatial
smoothening and the details (high frequency) are added using
bidirectional (temporal) predication of high frequency wavelet
coefficients. Finally inverse wavelet transform is applied on
modified wavelet coefficients to recover the frame. In proposed
algorithm, we carry out an automatic estimation of missing block
using spatio-temporal manner. Experiments are carried with
different YUV and compressed domain streams. The
experimental results show enhancement in PSNR as well as
visual quality and cross verified by video quality metrics (VQM).
Keywords—Error concealment; Wavelet Transform; Missing
Data estimation
I. INTRODUCTION
With enhancement in wired and wireless networks, more
and more users are demanding video services, including video
conferencing and video streaming over the internet. However,
the Internet does not provide guaranteed quality of service
(QoS). Loss of data packets occur due to traffic congestion
[1]. In wireless networks, packet loss happens frequently due
to shadowing, multipath fading, and noise disturbance of
wireless channels [3]. Video transmission uses compressed
video streams for transmission so that video data can be
transmitted even with poor network bandwidth situations [2].
A loss of packet over transmission in compressed stream
introduces severe distortion because the compression
algorithms use spatial estimation methods and temporal to
improve compression efficiency. Therefore a single distorted
block within a frame may occur errors not only in present
frame but also propagate error over several frames. Many
decoder error concealment techniques and error resilience
have been proposed to control amount of error in
reconstructed frame [4]. A simple error resilience approach is
to use feedback channels and request for retransmission
whenever there is error. This is the most prosperous technique
and the recovered data would always be correct. However, it
involves halting decoding process till error block of data is
received again. This is an inefficient approach in terms of
delay involved in process. Another way to avert errors is to
embed error checks in encoded video bit streams and transmit
over the channels. This method though bypasses
retransmission of video; it affects compression efficiency of
the encoder and thus increased usage of network bandwidth.
Hence, in this paper a post processing algorithms on the
decoder side are proposed for error concealment. The
preference with decoder error concealment is that it does not
require any change in encoding or decoding process. It simply
appends a post processing block which retrieves erroneous
data. Hence, there is no increase in bit rate or delay. Fig.1
shows block diagram for process in which packet loss occurs
in channel and video sequence to recover loss of macroblocks.
Therefore these methods can be used in real time video
applications like video-voice over internet and streaming
applications.
The complete video coding system can be organized
according to the blockdiagram in Fig. 2 The building blocks of
the video coding system including post processing at the
decoder are summarized below which give complete idea
about video coding system[17].
Video Acquisition—Source of the video sequence
which is output in a digital form. Following are the
processing steps.
Pre-Processing—Operations on the raw uncompressed
video source material, such as color correction, or de-
noising trimming, color format conversion.
Fig. 1. Block diagram of process in which packet loss occurs in channel