&lt;title&gt;Vector quantization of image pyramids with the ECPNN algorithm&lt;/title&gt;

Garrido, D.P. de; Pearlman, William A.; Finamore, Weiler A.

doi:10.1117/12.50307

Cited by 10 publications

(7 citation statements)

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“…The last point to be emphasized is that no loss of mean-squared-error performance occurred in previous coding simulations of data [1,2] and also in this work by the use of the ECPNN approach relative to the ECVQ approach. In both cases, the quantization search is identical, only the codebook design is different.…”

Section: Introductionmentioning

confidence: 66%

“…The same advantage occurs for the same reasons when comparing ECPNN and ECVQ in the single rate design case [2]. This occurs because of the simple calculations of the pairwise merging, when the initial size of the codebook is not too large (order of C = 212 vectors or less), and generates multiple codebooks in less time than the ECVQ algorithm.…”

Section: Introductionmentioning

confidence: 85%

“…EXkEX Xk Y II ->XkEX 'I Xk Y, It ] (1) and, P& = [ (n + n) 1og2(n + n) -n log2 n -n log2 nfl (2) where is the Eucidean norm of the vector, n is the cardinality of cluster and yi+1 is the vector resulted from the Mab operation. The cardinality of the cluster is the number of training vectors belonging to the cluster and is proportional to its estimated probability.…”

Section: Aecpnn Design Algorithmmentioning

confidence: 99%

“…By the other hand, a vector quantizer (VQ) that has the capabifity to sweep out the rate-distortion curve just using one codebook, can be called a multirate vector quantizer. Entropy-Constrained Vector Quantizer (ECVQ) [4] and Entropy-Constrained Pairwise-Nearest-Neighbor (ECPNN) [1,2] are examples of single rate VQ design algorithms, while Alphabet and Entropy-Constrained Vector Quantizer (AECVQ) [5] and Tree-Structured Vector Quantizer (TSVQ) [10] are examples of multirate VQ design algorithms. Except for TSVQ, the algorithms mentioned above belong to the class of full-search vectors quantizers.…”

Section: Introductionmentioning

confidence: 99%

“…The theoretical background of multirate vector quantization is presented in [3]. The objective of this paper is to present the extension of the ECPNN algorithm to the context of constrained alphabet and compare the results of coding image pyramids using this new approach with the previous results based on ECPNN [2] design. The new algorithm will be called Alphabet and Entropy-Constrained Pairwise-Nearest-Neighbor (AECPNN).…”

Section: Introductionmentioning

confidence: 99%

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<title>Image pyramid coding with multirate entropy-constrained pairwise nearest neighbor codebook design</title>

1992

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A new algorithm for multirate vector quantization is used for coding image pyramids. The algorithm, called alphabet-and entropy-constrained pairwise-nearest-neighbor (AECPNN), design codebooks choosing sub-codebooks from a large generic codebook. The algorithm is the natural extension of the ECPNN [1,2] design technique with constrained alphabet. Results of coded image pyramids of the present algorithm are comparable to the ECPNN design technique. 0-8194-081

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Section: Introductionmentioning

confidence: 66%

Section: Introductionmentioning

confidence: 85%

Section: Aecpnn Design Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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<title>Image pyramid coding with multirate entropy-constrained pairwise nearest neighbor codebook design</title>

1992

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Conditional entropy-constrained vector quantization: high-rate theory and design algorithms

Garrido

Pearlman

1995

IEEE Trans. Inform. Theory

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Transform coding of monochrome and color images using trellis coded quantization

Marcellin

Sriram

Tong

1993

IEEE Trans. Circuits Syst. Video Technol.

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The application of transform coding using trellis coded quantization (TCQ) to encode monochrome and color images is investigated. Specifically, TCQ is used to encode transform coefficients resulting from applying a 16 X 16 discrete cosine transform (DCT) to 8-b gray level and 24-b color images. For the color images, the red, green, and blue (RGB) planes are transformed into the NTSC transmission primaries (Y, I, and Q) before the DCT is applied. Rate allocation schemes for encoding the transform coefficients and side information are presented and discussed. The generalized Lloyd algorithm and the entropy-constrained vector quantizer design algorithm are used to design fixed-rate and entropy-constrained codebooks. The entropy-constrained designs result in a low-complexity system with objective performance rivaling that of many coding schemes from the literature.

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<title>Vector quantization of image pyramids with the ECPNN algorithm</title>

Cited by 10 publications

References 0 publications

<title>Image pyramid coding with multirate entropy-constrained pairwise nearest neighbor codebook design</title>

<title>Image pyramid coding with multirate entropy-constrained pairwise nearest neighbor codebook design</title>

Conditional entropy-constrained vector quantization: high-rate theory and design algorithms

Transform coding of monochrome and color images using trellis coded quantization

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