Video compression reduces the quantity of data used to represent digital video images through spatial image compression and temporal motion compensation. It is an example of source coding in information theory. Standard video compression techniques include H.120, H.261, MPEG-1, H.262/MPEG-2, H.263, MPEG-4, and H.264/AVC, which are used for applications like video conferencing, DVDs, broadcasting, and online video. H.264/AVC implements motion estimation and compensation algorithms through block-based motion prediction and a two-step search algorithm to further reduce file sizes, but these can result in block artifacts. The author aims to improve throughput and PSNR by implementing

2. Video compression - reducing the
quantity of data used to represent digital
video images.
It is a combination of spatial image
compression and temporal motion
compensation.
Video compression is an example of the
concept of source coding in Information
theory.

3. Video compression is needed for
transmission of good quality of video.
Compressed video can effectively reduce
the bandwidth required to transmit.
Transmission for longer range.
Optimizing data throughput—the
amount of data that will steadily move
through your playback pipeline and get
onto the screen.

4. Standard Publisher Popular Implementations
H.120 ITU - T
H.261 ITU - T Videoconferencing, Video
telephony
MPEG -1 Part 1 ISO, IEC Video - CD
H.262/MPEG-2 Part-2 ISO, IEC, ITU -T DVD Video, Blu -Ray, Digital
Video Broadcasting, SVCD
H.263 ITU - T Videoconferencing, Video
telephony & Video on
Mobile Phones
MPEG- 4 Part-2 ISO, IEC Video on Internet (DivX,
Xvid)
H.264/AVC/ MPEG-4 Part-10 ISO, IEC, ITU -T Blu – Ray, Digital Video
Broadcasting, iPod Video,
HD DVD

5. Generally Video Compression utilizes more
computational load and power.
In my work the main aim is to reduce the PSNR
such a way the throughput is improved which
in turn reduces the computational and power.

6. H.264/AVC is an Codec for Video Compression
As for this codec is concerned it is implemented in VLSI
architecture using some algorithms, such as
a) Motion Estimation Algorithm(or) Block based
motion compensation
b) Two Step Algorithm

7. • In motion estimation the frame is divided into macro
blocks.
• Full search Motion Estimation predicts the current MB
by finding the candidate that gives the minimum sum
of absolute difference(SAD).
• Two Step Algorithm
1) Truncating pixels for larger block sizes can result in
better motion prediction compared to smaller block
sizes.
2) At higher pixel resolutions, smaller block sizes can
result in better prediction compared to the larger block
sizes.

8. • But in this they have not concerned about the
noise that is persisting in the transformation.
• So in order improve the throughput and PSNR I
had idea to implement the same H.264/AVC
video compression using Edge Preserving
Algorithm which will reduce the block artifact.
• In EPA the approach is to preserve the detail of
image by using an edge protection map while
filtering blocky noise.
• The map is generated by pixel classification. Then
two adaptive filters to reduce noise.

9. • VHDL language, modelsim software, Xilinx

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Compression Architectures for Mobile Communication,” IEEE Trans. On Ckts.
and Syst. for video technology, Vol.19, No.9, Sep.2009.
[2]. Woong Hwangbo and Chong-Min Kyung, “A Multitransform Architecture for
H.264/AVC High-Profile Coders,” IEEE Trans. On Multimedia, Vol.12, No.3,
Apr.2010.
[3]. www.axis.com
[4]. Ihab Amer, Wael Badawy, Graham Jullien, Marco Mattavelli, Robert Turney, “
A Simplified 8 x 8 Transformation and Quantization Real-Time IP-Block for
MPEG-4, H.264/AVC Apllications: A new design Flow Approach,” Journal of
Ckts, Syst, and Comp. Vol.16, No.6, May 2008.