A comparison of vector quantization subband and transform coding of imagery

Fischer, Thomas R.; Blain, M.E.

doi:10.1109/iscas.1989.100647

Cited by 4 publications

(2 citation statements)

References 30 publications

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“…First the available bit-rate is sub-divided on the sub-images by taking into account both the variance of the coe cients and their correlation. 15 Then for each sub-image an allocation strategy is used to subdivide the available bits through the vectors to quantize the dimension of the vectors is always 64.…”

Section: Proposed Coding Schemementioning

confidence: 99%

<title>Comparison of different quantization strategies for subband coding of medical images</title>

1996

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In this paper di erent methods for the quantization of wavelet transform coe cients are compared in view of medical imaging applications. The goal is to provide users with a comprehensive and application oriented review of these techniques.Coding methods based on subband transforms are commonly used for image compression in a wide range of applications. In recent y ears, wavelet based methods have also been applied to medical images, and the rst commercial implementations of such techniques have appeared. 1 The issues related to clinical reliability o f processed images, together with additional features which will be o ered by future coding schemes render the conventional evaluation criteria e.g. PSNR insu cient. In this paper, the performance of four quantization methods namely standard Scalar Quantization , Embedded Zerotree, Variable Dimension Vector Quantization and Pyramid Vector Quantization are compared with regard to their application in the eld of medical imaging. In addition to the standard rate distortion criterion, we t o o k i n to account the possibility of bitrate control, the feasibility of real-time implementation, the genericity for use in non-dedicated multimedia environments of each approach. In addition, the diagnostical reliability of the decompressed images has been assessed during a viewing session and the help of a specialist.

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Section: Proposed Coding Schemementioning

confidence: 99%

<title>Comparison of different quantization strategies for subband coding of medical images</title>

1996

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“…Their better performances are mainly due to the fact that they take into account large image blocks, taking pro¯t this way of a larger amount of redundancies. A comparative study is provided in [4]. It shows the interest of Vector Quantization techniques when high compression rates are required (bit rate under 1 bit per pixel).…”

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confidence: 99%

Image compression using topological maps and MLP

Burel¹,

Catros²

IEEE International Conference on Neural Networks

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Jung

Burleson

1998

The Journal of VLSI Signal Processing

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A comparison of vector quantization subband and transform coding of imagery

Cited by 4 publications

References 30 publications

<title>Comparison of different quantization strategies for subband coding of medical images</title>

<title>Comparison of different quantization strategies for subband coding of medical images</title>

Image compression using topological maps and MLP

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