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Last Updated: Apr 25, 2025 | Study Period: 2023-2030
The Quanta Image Sensor (QIS) is a single-photon image sensor that produces binary values by oversampling the light field. It is the perfect option for the next generation image sensor after CMOS due to its single-photon sensitivity.
The sensor's picture reconstruction, however, continues to be a difficult problem. The majority of image reconstruction techniques in use today are optimised.
When given the binary bit stream from QIS as input, the deep neural network simultaneously learns the nonlinear transformation and denoising.
The Global Quanta Image Sensor market accounted for $XX Billion in 2022 and is anticipated to reach $XX Billion by 2030, registering a CAGR of XX% from 2023 to 2030.
In order to accurately detect individual photons in low light, Gigajot Technology introduced the first quanta image sensor (QIS), a brand-new imaging sensor with low noise capabilities.
At room temperature, maximum speed, and great dynamic range, the QIS can perform photon counting while maintaining efficiency.
It has a read noise reduction of 5â10 times more than that of typical small pixel image sensors, allowing it to operate in low light levels that were previously impossible for conventional image sensors.
Applications for imaging such as those in science, medicine, the military, industry, and space could make use of QIS products. In order to achieve 0.19 electron read noise at ambient temperature and less than 0.09 electron/second/pixel dark current, the 16 megapixel GJ01611 uses 1.1 micron pixels.
The second QIS component, the GJ00422, has a 4 megapixel sensor with a 2.20 micron pixel and has 0.27 electronic read noise with a single-exposure high dynamic range of 100 dB.
Their research efforts in astrophysics and quantum information science will be drastically changed by the capacity to count photons at ambient temperature.
The sensors are created using a cutting-edge stacked CMOS backside-illuminated (BSI) sensor manufacturing technique, which enables photon counting cameras to function at fast speeds and with little power.
The motion artefacts that are produced by traditional multi-exposure HDR techniques are minimised by single-exposure high dynamic range. For imaging in low light, single-photon detectors made by QIS are used.
Sl no | Topic |
1 | Market Segmentation |
2 | Scope of the report |
3 | Abbreviations |
4 | Research Methodology |
5 | Executive Summary |
6 | Introduction |
7 | Insights from Industry stakeholders |
8 | Cost breakdown of Product by sub-components and average profit margin |
9 | Disruptive innovation in the Industry |
10 | Technology trends in the Industry |
11 | Consumer trends in the industry |
12 | Recent Production Milestones |
13 | Component Manufacturing in US, EU and China |
14 | COVID-19 impact on overall market |
15 | COVID-19 impact on Production of components |
16 | COVID-19 impact on Point of sale |
17 | Market Segmentation, Dynamics and Forecast by Geography, 2023-2030 |
18 | Market Segmentation, Dynamics and Forecast by Product Type, 2023-2030 |
19 | Market Segmentation, Dynamics and Forecast by Application, 2023-2030 |
20 | Market Segmentation, Dynamics and Forecast by End use, 2023-2030 |
21 | Product installation rate by OEM, 2023 |
22 | Incline/Decline in Average B-2-B selling price in past 5 years |
23 | Competition from substitute products |
24 | Gross margin and average profitability of suppliers |
25 | New product development in past 12 months |
26 | M&A in past 12 months |
27 | Growth strategy of leading players |
28 | Market share of vendors, 2023 |
29 | Company Profiles |
30 | Unmet needs and opportunity for new suppliers |
31 | Conclusion |
32 | Appendix |