2022
DOI: 10.1177/15501329221083168
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A content awareness module for predictive lossless image compression to achieve high throughput data sharing over the network storage

Abstract: The idea of applying integer Reversible Colour Transform to increase compression ratios in lossless image compression is a well-established and widely used practice. Although various colour transformations have been introduced and investigated in the past two decades, the process of determining the best colour scheme in a reasonable time remains an open challenge. For instance, the overhead time (i.e. to determine a suitable colour transformation) of the traditional colour selector mechanism can take up to 50%… Show more

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Cited by 5 publications
(2 citation statements)
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“…where rect(t) � 1, |t| ≤ 1/2. Carry out vector quantization feature decomposition on the collected original multipose face image, and combine the gray manifold segmentation technology to extract the edge contour feature of the multipose face image, so as to improve the ability of face feature extraction [10].…”
Section: Multipose Face Image Acquisition Andmentioning
confidence: 99%
See 1 more Smart Citation
“…where rect(t) � 1, |t| ≤ 1/2. Carry out vector quantization feature decomposition on the collected original multipose face image, and combine the gray manifold segmentation technology to extract the edge contour feature of the multipose face image, so as to improve the ability of face feature extraction [10].…”
Section: Multipose Face Image Acquisition Andmentioning
confidence: 99%
“…T A irp represents the edge feature value of the input multipose face image; A irp represents the face feature value in the Delaunay triangle region; TR represents the pixel trace of multipose face image feature tracking recognition; W T i represents the relevant characteristic value of the nearest neighbor region [14]. e information restoration is performed according to the local features of the multipose face image, and the Potts prior parameter β i of the multipose face image feature detection is obtained as follows (10):…”
Section: Optimization Of Face Feature Extraction and Recognition Algo...mentioning
confidence: 99%