Model-guided measurement-side control for quantized block compressive sensing

doi:10.19682/j.cnki.1005-8885.2019.1009

中国邮电高校学报(英文) ›› 2019, Vol. 26 ›› Issue (2): 82-90.doi: 10.19682/j.cnki.1005-8885.2019.1009

Model-guided measurement-side control for quantized block compressive sensing

Tang Hainie, Liu Hao, Huang Rong, Deng Kailian, Sun Shaoyuan

College of Information Science and Technology, Donghua University, Shanghai 201620, China

收稿日期:2017-11-28 修回日期:2019-01-03 出版日期:2019-04-30 发布日期:2019-02-26
通讯作者: Corresponding author: Liu Hao, E-mail: liuhao@dhu.edu.cn E-mail:liuhao@dhu.edu.cn
作者简介:Corresponding author: Liu Hao, E-mail: liuhao@dhu.edu.cn
基金资助:
This work was supported by the Natural Science Foundation of Shanghai (18ZR1400300).

Model-guided measurement-side control for quantized block compressive sensing

Tang Hainie, Liu Hao, Huang Rong, Deng Kailian, Sun Shaoyuan

College of Information Science and Technology, Donghua University, Shanghai 201620, China

Received:2017-11-28 Revised:2019-01-03 Online:2019-04-30 Published:2019-02-26
Contact: Corresponding author: Liu Hao, E-mail: liuhao@dhu.edu.cn E-mail:liuhao@dhu.edu.cn
About author:Corresponding author: Liu Hao, E-mail: liuhao@dhu.edu.cn
Supported by:
This work was supported by the Natural Science Foundation of Shanghai (18ZR1400300).

摘要/Abstract

摘要： To progressively provide the competitive rate-distortion performance for aerial imagery, a quantized block compressive sensing (QBCS) framework is presented, which incorporates two measurement-side control parameters: measurement subrate (S) and quantization depth (D). By learning how different parameter
combinations may affect the quality-bitrate characteristics of aerial images, two parameter allocation models are derived between a bitrate budget and its appropriate parameters. Based on the corresponding allocation models, a model-guided image coding method is proposed to pre-determine the appropriate (S, D) combination for acquiring an aerial image via QBCS. The data-driven experimental results show that the proposed method can achieve near-optimal quality-bitrate performance under the QBCS framework.

关键词: block compressive sensing (BCS), measurement subrate, quantization depth, quality-bitrate, aerial image

Abstract: To progressively provide the competitive rate-distortion performance for aerial imagery, a quantized block compressive sensing (QBCS) framework is presented, which incorporates two measurement-side control parameters: measurement subrate (S) and quantization depth (D). By learning how different parameter
combinations may affect the quality-bitrate characteristics of aerial images, two parameter allocation models are derived between a bitrate budget and its appropriate parameters. Based on the corresponding allocation models, a model-guided image coding method is proposed to pre-determine the appropriate (S, D) combination for acquiring an aerial image via QBCS. The data-driven experimental results show that the proposed method can achieve near-optimal quality-bitrate performance under the QBCS framework.

Key words: block compressive sensing (BCS), measurement subrate, quantization depth, quality-bitrate, aerial image

中图分类号:

TN915.43

Tang Hainie, Liu Hao, Huang Rong, Deng Kailian, Sun Shaoyuan. Model-guided measurement-side control for quantized block compressive sensing[J]. The Journal of China Universities of Posts and Telecommunications, 2019, 26(2): 82-90.

参考文献

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Model-guided measurement-side control for quantized block compressive sensing

Model-guided measurement-side control for quantized block compressive sensing

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