On the Optimality of Embedded Deadzone Scalar-Quantizers for Wavelet-Based L-Infinite-Constrained Image Coding

Alecu, Alin; Munteanu, Adrian; Cornelis, Jan; Dewitte, Steven; Schelkens, Peter

doi:10.1109/lsp.2003.822599

Cited by 11 publications

(18 citation statements)

References 10 publications

(27 reference statements)

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“…If we take as the Euclidian distance between and , then (1) This shows that optimizing the rate allocation for a given MAXAD constraint is equivalent to finding a rate allocation such that the Hausdorff distance at that resolution is upper bounded by the MAXAD bound. One benefit of such mesh coding approach is that closed-form estimates of the L-infinite distortion are readily available, following for instance similar derivations as in our approach for L-infinite coding of images [24]- [26]. Based on this, fast algorithms to solve the R-D optimization problem can be designed.…”

Section: B Scalable L-infinite Coding Of Meshesmentioning

confidence: 99%

“…In other words, an L-infinite codec is capable to find the best rate allocation for which the L-infinite distortion (and consequently the Hausdorff distance) is upper-bounded by an user-defined bound, and guaranteed to be below that bound [24]- [26]. This is an interesting and unique feature in the context of 3-D object coding.…”

Section: B Scalable L-infinite Coding Of Meshesmentioning

confidence: 99%

“…As in (2), the MAXAD can be expressed as a linear combination of distortions occurring in the wavelet-domain, which are produced by scalar quantization of the wavelet subbands [24]- [26]. This relationship is well-known, and we have formulated it in the past for images and volumetric data [24], [25].…”

Section: Problem Formulationmentioning

confidence: 99%

“…It is important to observe that in the case of scalable waveletbased L-infinite-oriented coding, expression (2) is valid only for rates associated to a complete encoding of the corresponding bitplane in subband [24]- [26]. In other words, in the L-infinite case it is impossible to express for fractional bitplanes.…”

Section: Problem Formulationmentioning

confidence: 99%

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Scalable Joint Source and Channel Coding of Meshes

Cernea

Munteanu

Alecu

et al. 2008

IEEE Trans. Multimedia

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This paper proposes a new approach for joint source and channel coding (JSCC) of meshes, simultaneously providing scalability and optimized resilience against transmission errors. An unequal error protection approach is followed, to cope with the different error-sensitivity levels characterizing the various resolution and quality layers produced by the input scalable source codec. The number of layers and the protection levels to be employed for each layer are determined by solving a joint source and channel coding problem. In this context, a novel fast algorithm for solving the optimization problem is conceived, enabling a real-time implementation of the JSCC rate-allocation. An instantiation of the proposed JSCC approach is demonstrated for MeshGrid, which is a scalable 3-D object representation method, part of MPEG-4 AFX. In this context, the L-infinite distortion metric is employed, which is to our knowledge a unique feature in mesh coding. Numerical results show the superiority of the L-infinite norm over the classical L-2 norm in a JSCC setting. One concludes that the proposed joint source and channel coding approach offers resilience against transmission errors, provides graceful degradation, enables a fast real-time implementation, and preserves all the scalability features and animation capabilities of the employed scalable mesh codec.Index Terms-Error resilient coding, joint source and channel coding of meshes, L-infinite coding, MeshGrid, three-dimensional (3-D) graphics, unequal error protection.

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Section: B Scalable L-infinite Coding Of Meshesmentioning

confidence: 99%

Section: B Scalable L-infinite Coding Of Meshesmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

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Scalable Joint Source and Channel Coding of Meshes

Cernea

Munteanu

Alecu

et al. 2008

IEEE Trans. Multimedia

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“…In [25] and [26], a near-lossless compression proposal is introduced by refining pixel intervals, yielding a progressive -but not embedded-codestream. In [27], deadzone quantization was incorporated.…”

Section: Literature Overviewmentioning

confidence: 99%

A Fully Embedded Two-Stage Coder for Hyperspectral Near-Lossless Compression

Beerten

Blanes

Serra-Sagristà

2015

IEEE Geosci. Remote Sensing Lett.

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Abstract-This letter proposes a near-lossless coder for hyperspectral images. The coding technique is fully embedded and minimizes the distortion in the l2 norm initially and in the l∞ norm subsequently. Based on a two-stage near-lossless compression scheme, it includes a lossy and a near-lossless layer. The novelties are: the observation of the convergence of the entropy of the residuals in the original domain and in the spectral-spatial transformed domain; and an embedded near-lossless layer. These contributions enable a progressive transmission while optimising both SNR and PAE performance. The embeddedness is accomplished by bitplane encoding plus arithmetic encoding. Experimental results suggest that the proposed method yields a highly competitive coding performance for hyperspectral images, outperforming multi-component JPEG2000 for l∞ norm and pairing its performance for l2 norm, and also outperforming M-CALIC in the near-lossless case -for PAE ≥ 5-.

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