Line-based compressive sensing for low-power visual applications

TL;DR

This paper introduces a line-based compressive sensing scheme for low-power visual applications, reducing computational load and improving image quality during reconstruction compared to traditional methods.

Contribution

It proposes a novel line-based CS approach with an efficient reconstruction algorithm, enhancing image quality and reducing encoder complexity.

Findings

Improves image quality by 1dB to 3dB over conventional CS

Reduces computational complexity at encoder side

Enhances initial reconstruction quality

Abstract

In this paper, a Line based Compressive Sensing (LCS) scheme is discussed and proposed for low power visual applications, in which image acquisition is performed in a line-by-line manner at the encoder side using same measurement operator. Such approach reduces the computational burden and makes the implementation process easier (at encoder) plus provides better and more efficient initial reconstruction (at decoder) than other CS techniques. The reconstruction algorithm is based on the combination of the conventional augmented Lagrangian method with variable splitting and alternating direction method and is referred as TV-AL3. The simulation results show that the proposed line based CS scheme not only improves the quality of image by 1dB to ~3dB at various subrates, when compared to the conventional CS schemes but also reduces the computational complexity at the encoder side.