Compressive sensing for active imaging in SWIR spectral range

Paunescu, Gabriela; Lutzmann, Peter; Wegner, Daniel

doi:10.1117/12.2325377

Cited by 5 publications

(8 citation statements)

References 8 publications

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“…For each image, we use a number of patterns M = 16000; this corresponds to a compression ratio -expressed as a percentage -of M/N ~ 25%. The M patters are selected using the method C, "Image collection relevant patterns", described in [5]. A "relevance index" of a pattern is evaluated for a library of 64 images of arbitrary scenes and objects, then the N patterns are ordered by their averaged index and the first M patterns are selected.…”

Section: Methodsmentioning

confidence: 99%

“…Compressive sensing (CS) imaging [1][2][3][4][5] has the advantage of providing high resolution image acquisition using a detector with one or a few elements and a spatial light modulator. This can be a cost-effective solution to replace a highresolution camera or to make it available at all for frequency ranges that are not easily opened up.…”

Section: Introductionmentioning

confidence: 99%

“…Passive and active CS imaging systems have been developed and analyzed at IOSB during in-house and international collaborative programs [4][5][6][7][8]. CS measurements have been performed using coherent and non-coherent illumination sources in the visible and SWIR spectral ranges [5]. The encoding patterns based on Hadamard matrix have been selected via different methods.…”

Section: Introductionmentioning

confidence: 99%

“…The encoding patterns based on Hadamard matrix have been selected via different methods. A comparison of these approaches and an analysis of their advantages and disadvantages may be found in [5] and [8]. Indoor active CS experiments experiments using laser pulses at a wavelength of 1.55 µm with an energy of 4 µJ and a pulse width of 10 ns showed very good results at a range of 2.5 m [5].…”

Section: Introductionmentioning

confidence: 99%

“…A comparison of these approaches and an analysis of their advantages and disadvantages may be found in [5] and [8]. Indoor active CS experiments experiments using laser pulses at a wavelength of 1.55 µm with an energy of 4 µJ and a pulse width of 10 ns showed very good results at a range of 2.5 m [5]. For outdoor, longer distance applications, the atmospheric turbulence is expected to become a limiting factor.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Influence of turbulence on active compressive sensing imaging

Paunescu

Lutzmann²,

Wegner³

2022

Electro-Optical Remote Sensing XVI

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This paper presents experimental investigations on active compressive sensing imaging through turbulence. We developed a laboratory testbed in which different compressive sensing configurations have been tested under various turbulence conditions. Series of images of a target were acquired and analyzed using three different metrics. The measurements have been performed under continuous-wave laser illumination at 635 nm.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Influence of turbulence on active compressive sensing imaging

Paunescu

Lutzmann²,

Wegner³

2022

Electro-Optical Remote Sensing XVI

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CalibFPA: A Focal Plane Array Imaging System Based on Online Deep-Learning Calibration

Güngör,

Bahceci,

Ergen

et al. 2024

IEEE Trans. Comput. Imaging

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Scene-based Fourier pattern-sorting approach for compressive sensing

Limbach,

Eisele

2023

Emerging Imaging and Sensing Technologies for Security and Defence VIII

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In defense and security applications cost-intensive high-performance imaging sensors are common assets. Modern approaches in the field of Computational Imaging promise the cost-efficient construction of high-performance imaging sensors with additional features, like multitask or hyperspectral imaging capabilities. For example, the compressive single pixel imaging method we studied benefits from a low-cost architecture and multimodal sensor capabilities. The compressive single pixel imaging approach enables the adaption of resolution and compression at the cost of operational speed. The measurement process of an imaging system based on this approach involves a spatial modulation of the scene with a spatial light modulator utilizing different modulation patterns as well as a subsequent reconstruction step to obtain an image of the scene. The computational speed of the image reconstruction is still a problem, especially for the class of iterative optimization algorithms. For real-time applications like threat detection a fast image data acquisition and reconstruction are fundamental though. The fast reconstruction of the images via a fast and efficient transformation, e.g. the fast Fourier Transformation, is advantageous when using binary transformation-based modulation patterns. Therefore, we studied binary Fourier patterns and compared scene-based evolutionary and other sorting methods for transformation based single pixel imaging in order to maximize the compression while controlling the image degradation regarding relevant features to enable real-time applicability.

show abstract

Compressive sensing for active imaging in SWIR spectral range

Cited by 5 publications

References 8 publications

Influence of turbulence on active compressive sensing imaging

Influence of turbulence on active compressive sensing imaging

CalibFPA: A Focal Plane Array Imaging System Based on Online Deep-Learning Calibration

Scene-based Fourier pattern-sorting approach for compressive sensing

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