Super‐resolution approach to overcome physical limitations of imaging sensors: An overview

Choi, Euncheol; Choi, Jong Sun; Kang, Moon Gi

doi:10.1002/ima.20006

Cited by 24 publications

(21 citation statements)

References 39 publications

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“…In this case, the LED source is located at the origin of the coordinate axis. The luminous flux (Φ) of the LED light sources can be calculated by equation (2) as follows [9],…”

Section: Freeform Surface Lens Design Methodologymentioning

confidence: 99%

“…This is the reason for the 'white spot' (saturation of light) caused by the difference of luminous flux intensity between its center portion and outer frame [1]. Other distorted images may be caused by blooming and smearing that degrades image quality [2]. Also, most LED light patterns are circularly symmetric with non-uniform illuminance distribution.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Overall Illuminance Uniformity of IRED Lighting in Nighttime CCTV

Sa-Gong¹,

Park²,

Park³

et al. 2017

Transactions on Electrical and Electronic Materials

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This study looks at optimizinge light redistribution to improve the overall illuminance uniformity of commercial IRED modules. To obtain uniform illumination over a prescribed rectangular area, a freeform surface lens was evaluated using TracePro. The LED light overall illuminance uniformity regulated in KSC 7658 was verified using Relux software. Experimental test results showed 0.81 overall illuminance uniformity for rectangular light distribution of LED lights having a radiation angle of 80°. After fabricating prototype IRED lights based on these simulation results, illuminance performance was observed when used as actual IRED lighting with a nighttime CCTV system. Image observation photographs of the prototype 80° rectangular IRED lights confirmed that object images can be seen clearly owing to high overall illuminance uniformity, and that dark regions of the CCTV screen were not shown.

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“…In this case, the LED source is located at the origin of the coordinate axis. The luminous flux (Φ) of the LED light sources can be calculated by equation (2) as follows [9],…”

Section: Freeform Surface Lens Design Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Overall Illuminance Uniformity of IRED Lighting in Nighttime CCTV

Sa-Gong¹,

Park²,

Park³

et al. 2017

Transactions on Electrical and Electronic Materials

View full text Add to dashboard Cite

show abstract

“…Super-resolution (SR) imaging [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] aims to overcome or compensate the limitation or shortcomings of the image acquisition device/system and/or possibly ill-posed acquisition conditions to produce a higher-resolution image based on a set of images that were acquired from the same scene ( Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

A survey on super-resolution imaging

Tian

2011

SIViP

260

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The key objective of super-resolution (SR) imaging is to reconstruct a higher-resolution image based on a set of images, acquired from the same scene and denoted as 'low-resolution' images, to overcome the limitation and/or ill-posed conditions of the image acquisition process for facilitating better content visualization and scene recognition. In this paper, we provide a comprehensive review of SR image and video reconstruction methods developed in the literature and highlight the future research challenges. The SR image approaches reconstruct a single higher-resolution image from a set of given lower-resolution images, and the SR video approaches reconstruct an image sequence with a higher-resolution from a group of adjacent lower-resolution image frames. Furthermore, several SR applications are discussed to contribute some insightful comments on future SR research directions. Specifically, the SR computations for multi-view images and the SR video computation in the temporal domain are discussed.

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“…In [6], SROFM (Sub-pixel Resolving OptoFluidic Microscope) first applied the super-resolution (SR) image processing, which can generate one high-resolution (HR) image from one or multiple LR images. The SR algorithm in [6] is, however, based on the multi-frame image reconstruction, which needs to capture and store a large number (40 to 100) of subpixel-shifted LR cell images [7] with high complexity for on-chip implementation. In addition, as shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

A Single-Frame Superresolution Algorithm for Lab-on-a-Chip Lensless Microfluidic Imaging

Huang

Liu

et al. 2015

IEEE Des. Test

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With the recent advance of microfluidics-based lab-on-a-chip technology, lensless microfluidic imaging system with super-resolution (SR) has become a promising solution to miniaturize the conventional bulky lens-based microscope for high-throughput cell detection under specified resolution. The previous lensless system employing multi-frame SR processing limits the throughput due to the need to capture sub-pixel movement of capillary flowing cells. In this paper, we introduce two single-frame SR algorithms: one is interpolation-based method and the other one is machine-learning-based method. Both methods have shown great potential for on-chip implementation for cell detection with balanced resolution and throughput.

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Super‐resolution approach to overcome physical limitations of imaging sensors: An overview

Cited by 24 publications

References 39 publications

Overall Illuminance Uniformity of IRED Lighting in Nighttime CCTV

Overall Illuminance Uniformity of IRED Lighting in Nighttime CCTV

A survey on super-resolution imaging

A Single-Frame Superresolution Algorithm for Lab-on-a-Chip Lensless Microfluidic Imaging

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