The Journal of China Universities of Posts and Telecommunications ›› 2019, Vol. 26 ›› Issue (2): 82-90.doi: 10.19682/j.cnki.1005-8885.2019.1009

• Networks • Previous Articles     Next Articles

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

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

  1. 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:
  • About author:Corresponding author: Liu Hao, E-mail:
  • Supported by:
    This work was supported by the Natural Science Foundation of Shanghai (18ZR1400300).

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

CLC Number: