A Relative Imaging CMOS Image Sensor for High Dynamic Range and High Frame-Rate Machine Vision Imaging Applications

Katic, Nikola; Popović, Vladan; Cojbasic, Radisav; Schmid, Alexandre; Leblebici, Yusuf

doi:10.1109/jsen.2015.2413896

Cited by 8 publications

(7 citation statements)

References 14 publications

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“…By exploiting this property, we can state that the exact gradient is equal to: (4) where is the direction of the vector . Moreover, considering a generic versor , the following relation is valid:…”

Section: Methodsmentioning

confidence: 99%

“…In [4] several VLSI gradient extraction implementations have been reviewed. Such solutions deploy gradient magnitudes evaluations directly in a custom CMOS camera focal plane as preprocessing step.…”

Section: Introductionmentioning

confidence: 99%

“…Instead of evaluating an approximation of the Eq. (2) or deploying a custom circuitry as shown in [4], we rather propose a mathematical reformulation which offers a bounded approximation error with respect to the exact gradient. By modifying the number of bins, the resulting error is then controllable and deterministic.…”

Section: Introductionmentioning

confidence: 99%

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HOG-Dot: A Parallel Kernel-Based Gradient Extraction for Embedded Image Processing

Maggiani

Bourrasset

Petracca

et al. 2015

IEEE Signal Process. Lett.

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International audienceIn this paper we propose HOG-Dot, a method for the direct computation of the polar image gradients coordinates from the pixels values. The proposed algorithm, to be used as the first step of the Histogram of Oriented Gradient (HOG) pipeline, approximates the exact gradient with its projection onto a versor chosen among the projection plane set. Instead of non linear computations, the HOG-Dot method exploits linear operations while introducing a bounded approximation error with respect to other HOG approaches, thus resulting a more suitable solution for embedded devices. Concerning the state of the art, it also achieves improved accuracy with the mathematical spatial gradient formulation

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

HOG-Dot: A Parallel Kernel-Based Gradient Extraction for Embedded Image Processing

Maggiani

Bourrasset

Petracca

et al. 2015

IEEE Signal Process. Lett.

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show abstract

“…In [ 9 ], a two-dimensional (2D) adaptive dimming technique for an RGB-LED backlight is proposed to achieve a high dynamic contrast ratio. In [ 10 ], detection relative ratios capture scene features and patterns, resulting in an extremely high dynamic range. In [ 11 ], the video transmission system with autonomously controlled throughput is proposed.…”

Section: Introductionmentioning

confidence: 99%

Fast Control for Backlight Power-Saving Algorithm Using Motion Vectors from the Decoded Video Stream

Chen

Lin

et al. 2022

Sensors

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Backlight power-saving algorithms can reduce the power consumption of the display by adjusting the frame pixels with optimal clipping points under some tradeoff criteria. However, the computation for the selected clipping points can be complex. In this paper, a novel algorithm is created to reduce the computation time of the state-of-the-art backlight power-saving algorithms. If the current frame is similar to the previous frame, it is unnecessary to execute the backlight power-saving algorithm for the optimal clipping points, and the derived clipping point from the previous frame can be used for the current frame automatically. In this paper, the motion vector information was used as the measurement of the similarity between adjacent frames, where the generation of the motion vector information requires no extra complexity since it is generated to reconstruct the decoded frame pixels before the display. The experiments showed that the proposed work can reduce the running time of the state-of-the-art methods by 25.21% to 64.22%, while the performances are maintained; the differences with the state-of-the-art methods in PSNR are only 0.02~1.91 dB, and those in power are only −0.001~0.008 W.

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“…The rise of applications for new technologies such as artificial intelligence (AI), machine vision, and Internet-of-Things (IoT) has led to an increase on image sensor performance demands, for better data acquisition and analysis [1][2][3][4][5]. Those applications are known to have different requirements than the conventional applications of imaging for viewing and entertainment.…”

Section: Introductionmentioning

confidence: 99%

An Optical Filter-Less CMOS Image Sensor with Differential Spectral Response Pixels for Simultaneous UV-Selective and Visible Imaging

Silva

Kuroda

Sugawa

2019

Sensors

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This paper presents a complementary metal-oxide-semiconductor (CMOS) image sensor (CIS) capable of capturing UV-selective and visible light images simultaneously by a single exposure and without employing optical filters, suitable for applications that require simultaneous UV and visible light imaging, or UV imaging in variable light environment. The developed CIS is composed by high and low UV sensitivity pixel types, arranged alternately in a checker pattern. Both pixel types were designed to have matching sensitivities for non-UV light. The UV-selective image is captured by extracting the differential spectral response between adjacent pixels, while the visible light image is captured simultaneously by the low UV sensitivity pixels. Also, to achieve high conversion gain and wide dynamic range simultaneously, the lateral overflow integration capacitor (LOFIC) technology was introduced in both pixel types. The developed CIS has a pixel pitch of 5.6 µm and exhibits 172 µV/e − conversion gain, 131 ke − full well capacity (FWC), and 92.3 dB dynamic range. The spectral sensitivity ranges of the high and low UV sensitivity pixels are of 200-750 nm and 390-750 nm, respectively. The resulting sensitivity range after the differential spectral response extraction is of 200-480 nm. This paper presents details regarding the CIS pixels structures, doping profiles, device simulations, and the measurement results for photoelectric response and spectral sensitivity for both pixel types. Also, sample images of UV-selective and visible spectral imaging using the developed CIS are presented.

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A Relative Imaging CMOS Image Sensor for High Dynamic Range and High Frame-Rate Machine Vision Imaging Applications

Cited by 8 publications

References 14 publications

HOG-Dot: A Parallel Kernel-Based Gradient Extraction for Embedded Image Processing

HOG-Dot: A Parallel Kernel-Based Gradient Extraction for Embedded Image Processing

Fast Control for Backlight Power-Saving Algorithm Using Motion Vectors from the Decoded Video Stream

An Optical Filter-Less CMOS Image Sensor with Differential Spectral Response Pixels for Simultaneous UV-Selective and Visible Imaging

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