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video compression code using matlab in mpeg4 algorithm
#1

The main intention of video coding in most video
applications is to reduce the amount of video signal for
storing and/or transmission purposes without affecting
its visual quality. On root of quality, disks capacity and
bandwidth the desired video performance can be achieve.
For portable digital video applications, highly-integrated
real-time video compression and decompression
solutions are required. In reality motion estimation
based encoders are the most usually used in video
compression techniques. Such encoders make use of
inter-frame correlation to provide well-organized
compression. On the other hand Motion estimation
process is computationally expensive; its real time
implementation is tricky and pricey .
For stored video applications, motion-based video
coding standard MPEG (Moving Picture Experts Group)
was principally urbanized, where the encoding process
is typically carried out off-line on powerful computers.
So it is less suitable to implement as a real-time
compression technique for a portable recording or
communication device (video surveillance camera and
fully digital video cameras). In such applications,
efficient low cost/complexity implementation is the
most noteworthy issue. Thus, researchers turned towards
the design of new coders more adapted to new video
applications requirements which leads some researchers
to look for the exploitation of 3D transforms in order to
exploit temporal redundancy.
3D transform coder produces video compression
ratio which is close to the motion estimation based
coding one with less complex processing .
Redundancy has not the same pertinence since the
efficiency of 3D transform can reduce as pixel s values
variation in spatial or temporal dimensions is not
uniform. Often the temporal redundancies are more
relevant than spatial one [3]. In order to achieve
efficient compression by exploiting more and more the
redundancies in the temporal domain; this is the basic
purpose of the proposed technique. The proposed
technique consists on projecting temporal redundancy of
each group of pictures into spatial domain to be
combined with spatial redundancy in one representation
with high spatial correlation. The obtained
representation will be compressed as still image with
JPEG coder.
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#2

Dear

I'm Ruba i would like to learn more on video compression code using matlab in mpeg4 I am living in Jordan and i last studied in Yarmouk university and I'm working on a compression techniques

Thank u very much

Ruba Mfarij
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