A plug-n-play framework and acquisition methodology for remote exploration systems with single pixel cameras

Bhattacharjee, Protim; Börner, Anko

doi:10.1117/12.2525322

Cited by 2 publications

(11 citation statements)

References 8 publications

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“…2. For acquisition of the scene the three step acquisition methodology proposed in [7] is followed. The first step involves low resolution acquisition and it is performed using macro pixels formed by binning micromirrors of the DMD.…”

Section: Single Pixel Camera Model and Acquisition Methodology A Sing...mentioning

confidence: 99%

“…For example, in infrared imaging, one may use temperature as a parameter of detecting and segmenting RoIs; in visible wavelength imaging, one may use contrast of the scene. The third step of the algorithm in [7] is the sequential acquisition of RoIs detected in the second step at the full resolution of the DMD using multi-level sampling [12]. In this work we propose to estimate the change of information content in spatial scales of the RoIs and thus develop a procedure for step-by-step increase in the resolution of a RoI.…”

Section: Single Pixel Camera Model and Acquisition Methodology A Sing...mentioning

confidence: 99%

“…The three techniques described model the reconstruction problem in a manner that enables multiresolution recovery. In [7], the authors propose a different approach to acquisition in constrained systems; specifically, measurement-constrained systems. A three-step methodology is proposed that includes a low resolution acquisition and reconstruction step, RoI detection and segmentation step, and a multi-level sampling step to acquire RoIs in a scene.…”

Section: B Compressed Sensing For Constrained Systemsmentioning

confidence: 99%

“…The RI developed in the previous section is used to develop an acquisition algorithm for measurement-constrained systems. The three step sampling procedure discussed in [7] and elaborated in Sec. III is used as the basic framework for acquisition.…”

Section: B Adaptive Refinement Of Measurementsmentioning

confidence: 99%

See 3 more Smart Citations

Region-of-Interest Prioritised Sampling for Constrained Autonomous Exploration Systems

Bhattacharjee,

Burger,

Boerner

et al. 2021

Preprint

Self Cite

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Goal oriented autonomous operation of space rovers has been known to increase scientific output of a mission. In this work we present an algorithm, called the RoI Prioritised Sampling (RPS), that prioritises Region-of-Interests (RoIs) in an exploration scenario in order to utilise the limited resources of the imaging instrument on the rover effectively. This prioritisation is based on an estimator that evaluates the change in information content at consecutive spatial scales of the RoIs without calculating the finer scale reconstruction. The estimator, called the Refinement Indicator, is motivated and derived. Multiscale acquisition approaches, based on classical and multi-level compressed sensing, with respect to the single pixel camera architecture are discussed. The performance of the algorithm is verified on airborne sensor images and compared with the state-of-the-art multi-resolution reconstruction algorithms. At the considered sub-sampling rates the RPS is shown to better utilise the system resources for reconstructing the RoIs.

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Section: Single Pixel Camera Model and Acquisition Methodology A Sing...mentioning

confidence: 99%

Section: Single Pixel Camera Model and Acquisition Methodology A Sing...mentioning

confidence: 99%

Section: B Compressed Sensing For Constrained Systemsmentioning

confidence: 99%

Section: B Adaptive Refinement Of Measurementsmentioning

confidence: 99%

See 2 more Smart Citations

Region-of-Interest Prioritised Sampling for Constrained Autonomous Exploration Systems

Bhattacharjee,

Burger,

Boerner

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The RoI with the largest change is refined to a finer spatial resolution. With the help of the RI and the basic framework for sampling suggested in [7] for measurement-constrained systems an algorithm for multi-scale sampling is proposed and named RoI Prioritised Sampling (RPS). The RI provides a structured way to prioritise RoIs for acquisition at the cost of a small number of overhead measurements at each spatial resolution.…”

Section: Introductionmentioning

confidence: 99%

Region-of-Interest Prioritised Sampling for Constrained Autonomous Exploration Systems

Bhattacharjee

Burger

Boerner

2022

IEEE Trans. Comput. Imaging

View full text Add to dashboard Cite

Goal oriented autonomous operation of space rovers has been known to increase scientific output of a mission. In this work we present an algorithm, called the RoI Prioritised Sampling (RPS), that prioritises Region-of-Interests (RoIs) in an exploration scenario in order to utilise the limited resources of the imaging instrument on the rover effectively. This prioritisation is based on an estimator that evaluates the change in information content at consecutive spatial scales of the RoIs without calculating the finer scale reconstruction. The estimator, called the Refinement Indicator (RI), is motivated and derived. Multi-scale acquisition approaches, based on classical and multi-level compressed sensing, with respect to the single pixel camera architecture are discussed. The performance of the algorithm is verified on remote sensing images and compared with the state-of-the-art multi-resolution reconstruction algorithms. At the considered sub-sampling rates the RPS is shown to better utilise the system resources for reconstructing the RoIs.

show abstract

A plug-n-play framework and acquisition methodology for remote exploration systems with single pixel cameras

Cited by 2 publications

References 8 publications

Region-of-Interest Prioritised Sampling for Constrained Autonomous Exploration Systems

Region-of-Interest Prioritised Sampling for Constrained Autonomous Exploration Systems

Region-of-Interest Prioritised Sampling for Constrained Autonomous Exploration Systems

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