Vector quantization for entropy coding of image subbands

Senoo, T.; Girod, Bernd

doi:10.1109/83.199923

Cited by 78 publications

(16 citation statements)

References 25 publications

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“…Senoo and Girod examined the optimal allocation of bits among the various subhands [8], and their method is employed in the current work. They showed that the minimum overall distortion for a given total rate is achieved when the individual distortion rate curves D,(R,) are of equal slope, that is…”

Section: Bit Allocationmentioning

confidence: 99%

Tree-structured vector quantization with significance map for wavelet image coding

Cosman¹,

Perlmutter²,

Perlmutter³

Proceedings DCC '95 Data Compression Conference

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Variable-rate tree-structured VQ is applied to the coeficients obtained from an orthogonal wavelet decomposition. After encoding a vector, we examine the spatially corresponding vectors in the higher subbands to see whether or not they are "significant," that is, above some threshold. One bit of side inJformation is sent to the decoder to inform it of the result. When the higher bands are encoded, those vectors which were earlier marked as insignificant are not coded. An improved version of the algorithm makes the decision not to code vectors from the higher bands based on a distortion/rate trade08 rather than a strict thresholding criterion. Results of this method on the test image "Lena" yielded a PSNR of 30.15 dE at 0.174 bits per pixel.

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Section: Bit Allocationmentioning

confidence: 99%

Tree-structured vector quantization with significance map for wavelet image coding

Cosman¹,

Perlmutter²,

Perlmutter³

Proceedings DCC '95 Data Compression Conference

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“…Several advantages can be taken from these facts to efficiently design bit allocation and quantization strategies for the different subbands (Senoo and Girod, 1992;Jourdan and Alcaim, 1996). For object-based DWT coding, the number of significant edges is much lower than for regular images, since only one object is being coded (there are no contour edges).…”

Section: Introductionmentioning

confidence: 99%

Subband decomposition strategies for object‐based image coding

Souza

Acocella

Alcaim

2003

Int J Imaging Syst Tech

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ABSTRACT:In order to attain perfect reconstruction, subband decomposition of arbitrarily shaped objects requires special strategies to deal with the decimation problem. One of the two strategies described in this paper (scheme 1) inserts pixels with amplitudes equal to the mean values of the neighboring ones belonging to the object. The requirement of transmitting (coding) these pixels reduces the coding gain and is avoided by the second strategy (scheme 2) examined in this paper. This strategy determines specific values of the pixels added to the object in such a way that they result in predefined amplitudes after decimation. For this reason, this method outperforms scheme 1. PSNR versus bit rate are presented for two objects.

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“…In addition to the above methods, variable bit rate coding techniques have been used to take advantage of the burstiness of video sources and statistical multiplexing capability of asynchronous transfer mode (ATM) networks [11], [29], [37]. Other researchers have looked into the use of subband coding [10], [18], [25], [30] and wavelets for image compression [2], [3], [8], [40].…”

Section: Introductionmentioning

confidence: 99%

Enhancing videoconferencing using spatially varying sensing

Basu

Wiebe

1998

IEEE Trans. Syst., Man, Cybern. A

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Abstract-Human vision can be characterized as a variable resolution system-the region around the fovea (point of attention) is observed with great detail, whereas the periphery is viewed in lesser detail. In this work, we show that spatially varying sensing (resembling the human eye) can indeed be useful in videoconferencing. A system that can incorporate multiple and moving foveae is described. There are various possible ways of implementing multiple foveae and combining information from them. Some of these alternative strategies are discussed and results are compared. We also show the advantage of using spatially varying sensing as a preprocessor to JPEG. The methods described here can be useful in designing teleconferencing systems and image databases.

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Vector quantization for entropy coding of image subbands

Cited by 78 publications

References 25 publications

Tree-structured vector quantization with significance map for wavelet image coding

Tree-structured vector quantization with significance map for wavelet image coding

Subband decomposition strategies for object‐based image coding

Enhancing videoconferencing using spatially varying sensing

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