Discrete wavelet transforms (DWTs) applied temporally under motion
compensation (MC) have recently become a very powerful tool in video
compression, especially when implemented through lifting. A recent
theoretical analysis has established conditions for perfect reconstruction in the case of transversal MC-DWT, and also for the
equivalence of lifted and transversal implementations of MC-DWT. For
Haar MC-DWT these conditions state that motion must be invertible,
while for higher-order transforms they state that motion composition
must be a well-defined operator. Since many popular motion models do
not obey these properties, thus inducing errors (prior to compression), it is important to understand what is the impact of
motion non-invertibility or quasi-invertibility on the performance of
video compression. In this paper, we present new experimental results
of a study aiming at a quantitative evaluation of such impact in case
of block-based motion. We propose a new metric to measure the degree
with which two motion fields are not inverses of each other. Using
this metric we investigate several motion inversion schemes, from
simple temporal sample-and-hold, through spatial nearest-neighbor, to
advanced spline-based inversion, and we compare compression
performance of each method to that of independently-estimated forward
and backward motion fields. We observe that compression performance
monotonically improves with the reduction of the proposed motion
inversion error, up to 1-1.5dB for the advanced spline-based inversion. We also generalize the problem of "unconnected" pixels by
extending it to both update and prediction steps, as opposed to the
update step only used in conventional methods. Initial tests show
favorable results compared to previously reported techniques.
KEYWORDS: Quantization, Convolution, Motion estimation, 3D image processing, 3D scanning, Video, 3D modeling, Motion models, Video coding, 3D video compression
Two types of coders dominate the field of video compression research today: well-established hybrid coders, that are in the core of all MPEG and H.26X standards, and emerging three-dimensional (3D) subband coders, largely inspired by the success of wavelet-based still image compression. However, there are surprisingly few results reported on 3D Discrete Cosine Transform (DCT) based transform coders. Even while exploiting all the benefical properties of the DCT itself (forward/inverse symmetry, fast separable implementation, and excellent energy compaction), these coders under-perform when compared to competing hybrid coders primarily due to
ineffcient quantization, scanning and entropy coding used. In this paper, we study means of improving 3D-DCT coding by proposing adaptive scanning order and quantization of coeffcients that are better matched to 3D-DCT spectrum of a motion sequence. Our results show signifcant improvement in performance over previously
reported techniques.
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