Efficiency of shape-adaptive 2-D transforms for coding of arbitrarily shaped image segments

Sikora, Thomas; Bauer, Sebastian; Makai, B.

doi:10.1109/76.401104

Cited by 47 publications

(28 citation statements)

References 5 publications

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“…However, for video-coding applications Gilge's "shape-adapted" DCT 11, 12 based on orthonormalization with respect to shape is known to achieve superior results than the approach by Sikora et al It is considered 30 as a kind of upper bound on the decorrelation ability of the faster method. Thus, if computational complexity is not of primary concern, Gilge's method may be utilized as an alternative method to achieve further improvement in denoising.…”

Section: Gilge's "Shape-adapted" Dct By Orthogonalizationmentioning

confidence: 99%

Shape-adaptive DCT for denoising and image reconstruction

et al. 2006

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The shape-adaptive DCT (SA-DCT) can be computed on a support of arbitrary shape, but retains a computational complexity comparable to that of the usual separable block DCT. Despite the near-optimal decorrelation and energy compaction properties, application of the SA-DCT has been rather limited, targeted nearly exclusively to video compression. It has been recently proposed by the authors 8 to employ the SA-DCT for still image denoising. We use the SA-DCT in conjunction with the directional LPA-ICI technique, which defines the shape of the transform's support in a pointwise adaptive manner. The thresholded or modified SA-DCT coe cients are used to reconstruct a local estimate of the signal within the adaptive-shape support. Since supports corresponding to di erent points are in general overlapping, the local estimates are averaged together using adaptive weights that depend on the region's statistics. In this paper we further develop this novel approach and extend it to more general restoration problems, with particular emphasis on image deconvolution. Simulation experiments show a state-of-the-art quality of the final estimate, both in terms of objective criteria and visual appearance. Thanks to the adaptive support, reconstructed edges are clean, and no unpleasant ringing artifacts are introduced by the fitted transform.

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Section: Gilge's "Shape-adapted" Dct By Orthogonalizationmentioning

confidence: 99%

Shape-adaptive DCT for denoising and image reconstruction

et al. 2006

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“…For simplicity, we assume 2D separability and stationarity as in references [6], [9] and [10]. A more realistic 2D non separable, noncausal, and non-stationary model has been considered already for rectangular-shaped fields [11]- [ 13], but it has not been done yet for arbitrarily-shaped fields.…”

Section: The Optimum Sa Transformmentioning

confidence: 99%

A Distance Measure for Perfoemance Evaluation of Shape Adaptive Transforms

Acocella¹,

Alcaim²

2005

Journal of Communication and Information Systems

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“…Note that the Decision algorithm has selected a quite different strategy for the two bit rates: for low bit rates almost 20% of the bit stream is devoted to the partition information, whereas less than 10% is used for this type of information for higher bit rates. Finally, let us mention that by comparison with the algorithm presented in [32] using a much simpler bit allocation rule, the current algorithm provides between 2 and 3 dB of PSNR for very low bit rates (30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40).…”

Section: A Coding Efficiencymentioning

confidence: 99%

“…In particular, three different texture coding techniques have been used: polynomial approximation onto orthogonal bases [8], shape-adaptive discrete cosine transform (DCT) [35], [10], and region-based wavelets. For the first technique, cosine basis functions have been chosen as orthogonal bases given that they have proved to often outperform polynomial functions.…”

Section: ) Texture Motion Compensationmentioning

confidence: 99%

Segmentation-based video coding system allowing the manipulation of objects

Salembier

Marqués

Pardàs

et al. 1997

IEEE Trans. Circuits Syst. Video Technol.

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Abstract-This paper presents a generic video coding algorithm allowing the content-based manipulation of objects. This manipulation is possible thanks to the definition of a spatiotemporal segmentation of the sequences. The coding strategy relies on a joint optimization in the rate-distortion sense of the partition definition and of the coding techniques to be used within each region. This optimization creates the link between the analysis and synthesis parts of the coder. The analysis defines the time evolution of the partition, as well as the elimination or the appearance of regions that are homogeneous either spatially or in motion. The coding of the texture as well as of the partition relies on region-based motion compensation techniques. The algorithm offers a good compromise between the ability to track and manipulate objects and the coding efficiency.

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Efficiency of shape-adaptive 2-D transforms for coding of arbitrarily shaped image segments

Cited by 47 publications

References 5 publications

Shape-adaptive DCT for denoising and image reconstruction

Shape-adaptive DCT for denoising and image reconstruction

A Distance Measure for Perfoemance Evaluation of Shape Adaptive Transforms

Segmentation-based video coding system allowing the manipulation of objects

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