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Motion estimation techniques are widely used in today''s video
processing systems. The most frequently used techniques are the
block matching and the differential method. In the first part
of this thesis, we have studied this topic form a viewpoint
different from the above to explore the fundamental limits and
tradeoffs in image motion estimation. The underlying principles
behind two conflict requirements in motion estimation, accuracy
and ambiguity, become clear when they are analyzed using this
tool --- frequency component analysis. This analysis also
suggests new motion estimation algorithm and ways to improve the
existing algorithms. Ths so-called frequency component motion
estimation algorithm is thus proposed. Comparing to the
conventional block matching and phase correlation algorithms,
this approach provides more reliable displacement estimates
particularly for the noisy pictures. In a conventional motion-
compensated coding scheme, images are often partitioned into
artificial units such as rectangular blocks. Without
considering the natural spatio-temporal structure of images and
the characteristics of human visual system, the performance of
block based motion compensation is often limited by this
fundamental restriction. In addition, this coding structure
does not match the object scalability requirement which is a new
trend in video coding. Thus, in the second part of this thesis,
we develop several techniques to form a new deformable mesh
video coding algorithm. These techniques include foreground/
background separation, nodal point tracking with overlapped
patch elimination, and nonrectangular DCT coding schemes. The
simulation results indicate that this coding structure is quite
suitable for object scalable coding at low bit rates.
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