2006
DOI: 10.1016/j.image.2006.03.011
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Motion estimation and compensation in the redundant-wavelet domain using triangle meshes

Abstract: In this paper, a technique is presented that incorporates an irregular triangle mesh into wavelet-domain motion estimation and compensation using a shift-invariant redundant-wavelet transform. The main contribution of this work resides in a demonstration that triangle-mesh motion estimation and compensation can be deployed more effectively in the redundant-wavelet domain thanks to a simple correlation operator that is robust to the prediction residual, a noise-like signal that hinders spatial-domain gradient-b… Show more

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Cited by 8 publications
(3 citation statements)
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“…The correlation mask consists of multiplying the high-low (HL) bands, the low-high (LH) bands, and the high-high (HH) bands together and combining the products [2][3] :…”
Section: Extraction Feature Pointsmentioning
confidence: 99%
“…The correlation mask consists of multiplying the high-low (HL) bands, the low-high (LH) bands, and the high-high (HH) bands together and combining the products [2][3] :…”
Section: Extraction Feature Pointsmentioning
confidence: 99%
“…Motion into subsequent frames is estimated by centering a small block at each vertex in the first frame of the GOF and finding the best matching block in the current frame. We search for the motion of the vertices by minimizing a distortion metric that spans across all subbands of the RDWT decomposition, as we did in [12,13]. Assuming that a GOF contains G frames, this ME process results in G − 1 motion fields, each mapping the first frame of the GOF into one of the other G − 1 frames of the GOF, as illustrated in Fig.…”
Section: The 3d-rwmh Systemmentioning
confidence: 99%
“…The most likely explanation for the existence of correlation is the inherent spectral features of the noise and the non-orthonormality of TIDWT. This unique interaction property between coefficients and TIDWT is perhaps one of the contributions to the success of waveletdomain motion estimation[141,142]. Here, for denoising applications, we incorporated a correlation limit in the LD threshold to handle this association characteristic between coefficients, with the aim to optimize noise cancellation in translation invariance domain.To determine the correlation limit in the proposed LCD threshold, we examined all the possible correlations in the TIDWT domain.…”
mentioning
confidence: 99%