**Part 2**

**Motion Estimation** 

54 Video Compression

Young, D., Yen, J., Petitti, F., Bakir, T., Brennan, M., and Butto, R. 2009. Video National

Young, D., Bakir, T., Butto, R., Duffield, C., and Petitti, F. 2010a. Loss of Interpretability Due

Young, D., Bakir, T., Butto, R., and Petitti, F. 2010b. Factors Related to Low Slant Angle Affecting Airborne Video Interpretability, *Proceedings of the SPIE,* San Diego, 7668.

*SPIE,* San Diego, 7307.

*SPIE*, 7529.

Imagery Interpretability Rating Scale Cirterial Survey Results, *Proceedings of the* 

to Compression Effects as Measured by the New Video NIIRS, *Proceedings of the* 

**4** 

*India* 

**H.264 Motion Estimation and Applications** 

A video signal represented as a sequence of frames of pixels contains vast amount of redundant information that can be eliminated with video compression technology enhancing the total transmission and hence storage becomes more efficient. To facilitate interoperability between compression at the video producing source and decompression at the consumption end, several generations of video coding standards have been defined and adapted by the ITU-G and VCEG etc... Demand for high quality video is growing exponentially and with the advent of the new standards like H.264/AVC it has placed a significant increase in programming and computational power of the processors. In H.264/AVC, the motion estimation part holds the key in capturing the vital motion vectors for the incoming video frames and hence takes very high processing at both encoder and the decoder. This chapter gives an overview of Motion estimation and the various search algorithms and also the scalability of parallelism in their operations to enhance the performance and improve the overall video quality. For low-end applications, software solutions are adequate. For high-end applications, dedicated hardware solutions are needed. This chapter gives an overview of H.264/AVC video coding in general and its applications in four main sections. Section 1 deals with motion estimation and the types of algorithms one of the key modules of H.264 and the most time-consuming. Section 2 deals with the estimation criterion and their role in determining the complexiety of the estimation algorithms. Section 3 briefly discusses about the scalability of parallelism in H.264 and the final section deals with the applications of H.264 focussing on Aerial video surveillance and

Motion estimation techniques form the core of H.264/AVC (Iain Richardson, 2010) video compression and video processing applications. It extracts motion information from the video sequence where the motion is typically represented using a motion vector (x, y). The motion vector indicates the displacement of a pixel or a pixel block from the current location due to motion. This information is used in video compression to find best matching block in reference frame to calculate low energy residue to generate temporally interpolated frames. It is also used in applications such motion compensated de-interlacing, video stabilization, motion tracking etc. Varieties of motion estimation techniques are available. There are pelrecursive techniques, which derive motion vector (T.Wiegand et.al, 2003) for each pixel and

**1. Introduction**

its advantages.

**1.1 Motion estimation** 

Murali E. Krishnan, E. Gangadharan and Nirmal P. Kumar

*Anand Institute of Higher Technology, Anna University,* 
