A sur-pixel scan method for super-resolution reconstruction

Sun, Mingjie; Yu, Kun

doi:10.1016/j.ijleo.2013.05.131

Cited by 7 publications

(2 citation statements)

References 9 publications

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“…However, apart from the technological challenges associated with this approach, smaller pixels detect less light, which degrades image quality [1]. An alternative approach to increase the pixel resolution is microscanning [2][3][4][5][6]. In this approach, multiple images of the same scene are recorded, and the pixelated detector is displaced by sub-pixel sized translations between each images.…”

Section: Introductionmentioning

confidence: 99%

Improving the signal-to-noise ratio of single-pixel imaging using digital microscanning

et al. 2016

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Single-pixel cameras provide a means to perform imaging at wavelengths where pixelated detector arrays are expensive or limited. The image is reconstructed from measurements of the correlation between the scene and a series of masks. Although there has been much research in the field in recent years, the fact that the signal-to-noise ratio (SNR) scales poorly with increasing resolution has been one of the main limitations prohibiting the uptake of such systems. Microscanning is a technique that provides a final higher resolution image by combining multiple images of a lower resolution. Each of these low resolution images is subject to a sub-pixel sized lateral displacement. In this work we apply a digital microscanning approach to an infrared single-pixel camera. Our approach requires no additional hardware, but is achieved simply by using a modified set of masks. Compared to the conventional Hadamard based single-pixel imaging scheme, our proposed framework improves the SNR of reconstructed images by ∼ 50 % for the same acquisition time. In addition, this strategy also provides access to a stream of low-resolution 'preview' images throughout each high-resolution acquisition.

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Section: Introductionmentioning

confidence: 99%

Improving the signal-to-noise ratio of single-pixel imaging using digital microscanning

et al. 2016

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“…Wu [ 18 ] designed a rotary micro-scanner, which can effectively improve the spatial resolution of infrared images and improve the function value of the system. Sun and Yu [ 19 ] believed that sub-pixel scanning via mobile sensors would be the key to SR reconstruction. They proposed a sur-pixel scanning method with low processing difficulty, which verified its advantages in engineering.…”

Section: Techniques For Improving the Resolution Of Remote-sensingmentioning

confidence: 99%

High-Efficiency Microsatellite-Using Super-Resolution Algorithm Based on the Multi-Modality Super-CMOS Sensor

Zhang

Yang

et al. 2020

Sensors

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To realize the application of super-resolution technology from theory to practice, and to improve microsatellite spatial resolution, we propose a special super-resolution algorithm based on the multi-modality super-CMOS sensor which can adapt to the limited operation capacity of microsatellite computers. First, we designed an oblique sampling mode with the sensor rotated at an angle of 26.56 ∘ ( arctan 1 2 ) to obtain high overlap ratio images with sub-pixel displacement. Secondly, the proposed super-resolution algorithm was applied to reconstruct the final high-resolution image. Because the satellite equipped with this sensor is scheduled to be launched this year, we also designed the simulation mode of conventional sampling and the oblique sampling of the sensor to obtain the comparison and experimental data. Lastly, we evaluated the super-resolution quality of images, the effectiveness, the practicality, and the efficiency of the algorithm. The results of the experiments showed that the satellite-using super-resolution algorithm combined with multi-modality super-CMOS sensor oblique-mode sampling can increase the spatial resolution of an image by about 2 times. The algorithm is simple and highly efficient, and can realize the super-resolution reconstruction of two remote-sensing images within 0.713 s, which has good performance on the microsatellite.

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A novel method for subdivided locating of star image in star identification

Zhou

Shi

2015

Optik

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A sur-pixel scan method for super-resolution reconstruction

Cited by 7 publications

References 9 publications

Improving the signal-to-noise ratio of single-pixel imaging using digital microscanning

Improving the signal-to-noise ratio of single-pixel imaging using digital microscanning

High-Efficiency Microsatellite-Using Super-Resolution Algorithm Based on the Multi-Modality Super-CMOS Sensor

A novel method for subdivided locating of star image in star identification

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