Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid Encoding
<p/> <p>Many common modalities of medical images acquire high-resolution and multispectral images, which are subsequently processed, visualized, and transmitted by subsampling. These subsampled images compromise resolution for processing ability, thus risking loss of significant diagnost...
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Online Access: | http://dx.doi.org/10.1155/S1110865703211203 |
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doaj-ed09e1ec7d3c47a0ba8a4cc1fad4b5b82020-11-24T20:48:15ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61721687-61802003-01-0120035619364Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid EncodingLee DJYang ShuyuMitra SunandaCorona EnriqueNutter Brian<p/> <p>Many common modalities of medical images acquire high-resolution and multispectral images, which are subsequently processed, visualized, and transmitted by subsampling. These subsampled images compromise resolution for processing ability, thus risking loss of significant diagnostic information. A hybrid multiresolution vector quantizer (HMVQ) has been developed exploiting the statistical characteristics of the features in a multiresolution wavelet-transformed domain. The global codebook generated by HMVQ, using a combination of multiresolution vector quantization and residual scalar encoding, retains edge information better and avoids significant blurring observed in reconstructed medical images by other well-known encoding schemes at low bit rates. Two specific image modalities, namely, X-ray radiographic and magnetic resonance imaging (MRI), have been considered as examples. The ability of HMVQ in reconstructing high-fidelity images at low bit rates makes it particularly desirable for medical image encoding and fast transmission of 3D medical images generated from multiview stereo pairs for visual communications.</p>http://dx.doi.org/10.1155/S1110865703211203high fidelity hybrid encodingglobal codebooklow bit ratemultilevel wavelet feature statisticsefficient retrieval of high-resolution medical images |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Lee DJ Yang Shuyu Mitra Sunanda Corona Enrique Nutter Brian |
spellingShingle |
Lee DJ Yang Shuyu Mitra Sunanda Corona Enrique Nutter Brian Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid Encoding EURASIP Journal on Advances in Signal Processing high fidelity hybrid encoding global codebook low bit rate multilevel wavelet feature statistics efficient retrieval of high-resolution medical images |
author_facet |
Lee DJ Yang Shuyu Mitra Sunanda Corona Enrique Nutter Brian |
author_sort |
Lee DJ |
title |
Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid Encoding |
title_short |
Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid Encoding |
title_full |
Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid Encoding |
title_fullStr |
Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid Encoding |
title_full_unstemmed |
Multilevel Wavelet Feature Statistics for Efficient Retrieval, Transmission, and Display of Medical Images by Hybrid Encoding |
title_sort |
multilevel wavelet feature statistics for efficient retrieval, transmission, and display of medical images by hybrid encoding |
publisher |
SpringerOpen |
series |
EURASIP Journal on Advances in Signal Processing |
issn |
1687-6172 1687-6180 |
publishDate |
2003-01-01 |
description |
<p/> <p>Many common modalities of medical images acquire high-resolution and multispectral images, which are subsequently processed, visualized, and transmitted by subsampling. These subsampled images compromise resolution for processing ability, thus risking loss of significant diagnostic information. A hybrid multiresolution vector quantizer (HMVQ) has been developed exploiting the statistical characteristics of the features in a multiresolution wavelet-transformed domain. The global codebook generated by HMVQ, using a combination of multiresolution vector quantization and residual scalar encoding, retains edge information better and avoids significant blurring observed in reconstructed medical images by other well-known encoding schemes at low bit rates. Two specific image modalities, namely, X-ray radiographic and magnetic resonance imaging (MRI), have been considered as examples. The ability of HMVQ in reconstructing high-fidelity images at low bit rates makes it particularly desirable for medical image encoding and fast transmission of 3D medical images generated from multiview stereo pairs for visual communications.</p> |
topic |
high fidelity hybrid encoding global codebook low bit rate multilevel wavelet feature statistics efficient retrieval of high-resolution medical images |
url |
http://dx.doi.org/10.1155/S1110865703211203 |
work_keys_str_mv |
AT leedj multilevelwaveletfeaturestatisticsforefficientretrievaltransmissionanddisplayofmedicalimagesbyhybridencoding AT yangshuyu multilevelwaveletfeaturestatisticsforefficientretrievaltransmissionanddisplayofmedicalimagesbyhybridencoding AT mitrasunanda multilevelwaveletfeaturestatisticsforefficientretrievaltransmissionanddisplayofmedicalimagesbyhybridencoding AT coronaenrique multilevelwaveletfeaturestatisticsforefficientretrievaltransmissionanddisplayofmedicalimagesbyhybridencoding AT nutterbrian multilevelwaveletfeaturestatisticsforefficientretrievaltransmissionanddisplayofmedicalimagesbyhybridencoding |
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1716808436104036352 |