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Emerging Image Sensor Technologies 2024-2034: Applications and Markets


新たなイメージセンサー技術 2024-2034:用途と市場

この調査レポートは、様々な解像度と波長感度を持つ最も多様なイメージセンサーを評価しています。   主な掲載内容(目次より抜粋) 市場予測 可視域イメージセンサー ... もっと見る

 

 

出版社 出版年月 電子版価格 ページ数 言語
IDTechEx
アイディーテックエックス
2023年9月20日 US$7,000
電子ファイル(1-5ユーザライセンス)
ライセンス・価格情報
注文方法はこちら
381 英語

※ 調査会社の事情により、予告なしに価格が変更になる場合がございます。


 

Summary

この調査レポートは、様々な解像度と波長感度を持つ最も多様なイメージセンサーを評価しています。
 
主な掲載内容(目次より抜粋)
  • 市場予測
  • 可視域イメージセンサー
  • 短波長赤外線イメージセンサー
  • ハイブリッドイメージセンサー
  • 薄膜受光素子
  • 小型分光法
  • X線イメージセンサー
  • 量子イメージセンサー
  • 会社概要
 
Report Summary
IDTechEx's "Emerging Image Sensor Technologies 2024-2034: Applications and Markets" report evaluates the most diverse range of image sensors with varying resolutions and wavelength sensitivities. This technology is set to impact multiple industries from healthcare, biometrics, autonomous driving, agriculture, chemical sensing, and food inspection, among several others. The growing importance of these technologies is expected to contribute towards the growth of this market, with projections of it reaching US$739 million by 2034. This figure is, in fact, conservative because a much larger market value is predicted if these sensors take-off I the consumer electronics sector. As an example, the QD-on-CMOS market would note a 25X increase in revenue value if the consumer electronics space is considered.
 
Primary insight from interviews with individual players, ranging from established players to innovative start-ups, is included alongside 25 detailed company profiles that include discussion of both technology and business models and SWOT analysis. Additionally, the report includes technological and commercial readiness assessments, split by technology and application. It also discusses the commercial motivation for developing and adopting each of the emerging image sensing technologies and evaluates the barriers to entry.
 
Figure: Overview of emerging sensing technologies covered in this report.
 
Fundamental topics are covered throughout this report including the evaluation of individual technology readiness levels as well as detailed SWOT analyses for each technology.
 
From these insights it is possible to predict which technologies are most likely to succeed and which companies have positioned themselves in a more competitive position to thrive in the market.
 
This report also covers different applications that will benefit from these technologies as well as key challenges they may face in commercializing their products. The rate at which autonomy develops, for instance, will be partly dependent on the maturity of these sensors in the medium to long-term. Increased sensor maturity is synonymous with more cost effective and advanced technology, i.e., more sensitive sensors.
 
Emerging Image Sensors Go Beyond Visible/IR
While conventional CMOS detectors for visible light are well established and somewhat commoditized, at least for low value applications, there is an extensive opportunity for more complex image sensors that offer capabilities beyond that of simply acquiring red, green, and blue (RGB) intensity values. As such, extensive effort is currently being devoted to developing emerging image sensor technologies that can detect aspects of light beyond human vision. This includes imaging over a broader spectral range, over a larger area, acquiring spectral data at each pixel, and simultaneously increasing temporal resolution and dynamic range.
 
Much of this opportunity stems from the ever-increasing adoption of machine vision, in which image analysis is performed by computational algorithms. Machine learning requires as much input data as possible to establish correlations that can facilitate object identification and classification, so acquiring optical information over a different wavelength range, or with spectral resolution for example, is highly advantageous.
 
Emerging image sensor technologies offer many other benefits. Depending on the technology this can include similar capabilities at a lower cost, increased dynamic range, improve temporal resolution, spatially variable sensitivity, global shutters at high resolution, reducing the unwanted influence of scattering, flexibility/conformality, and more. A particularly important trend is the development of much cheaper alternatives to very expensive InGaAs sensors for imaging in the short-wave infra-red (SWIR, 1000-2000 nm) spectral region, which will open this capability to a much wider range of applications. This includes autonomous vehicles, in which SWIR imaging assists with distinguishing objects/materials that appear similar in the visible spectrum, while also reducing scattering from dust and fog.
 
There are several competitive emerging SWIR technologies. These include hybrid image sensors where an additional light absorbing thin film layer made of organic semiconductors or quantum dots is placed on top of a CMOS read-out circuit to increase the wavelength detection range into the SWIR region. Another technology is extended-range silicon where the properties of silicon are modified to extend the absorption range beyond its bandgap limitations. Currently dominated by expensive InGaAs sensors, these new approaches promise a substantial price reduction which is expected to encourage the adoption of SWIR imaging for new applications such as autonomous vehicles.
 
Obtaining as much information as possible from incident light is highly advantageous for applications that require object identification, since classification algorithms have more data to work with. Hyperspectral imaging, in which a complete spectrum is acquired at each pixel to product an (x, y, λ) data cube using a dispersive optical element and an image sensor, is a relatively established technology that has gained traction for precision agriculture and industrial process inspection. However, at present most hyperspectral cameras work on a line-scan principle, while SWIR hyperspectral imaging is restricted to relatively niche applications due to the high cost of InGaAs sensors that can exceed US$50,000. Emerging technologies using silicon or thin film materials look set to disrupt both these aspects, with snapshot imaging offering an alternative to line-scan cameras and with the new SWIR sensing technologies method facilitating cost reduction and adoption for a wider range of applications.
 
Another emerging image sensing technology is event-based vision, also known as dynamic vision sensing (DVS). Autonomous vehicles, drones and high-speed industrial applications require image sensing with a high temporal resolution. However, with conventional frame-based imaging a high temporal resolution produces vast amounts of data that requires computationally intensive processing. Event-based vision is an emerging technology that resolves this challenge. It is a completely new way of thinking about obtaining optical information, in which each sensor pixel reports timestamps that correspond to intensity changes. As such, event-based vision can combine greater temporal resolution of rapidly changing image regions, with much reduced data transfer and subsequent processing requirements.
 
The report also looks at the burgeoning market of miniaturized spectrometers. Driven by the growth in smart electronics and Internet of Things devices, low-cost miniaturized spectrometers are becoming increasingly relevant across different sectors. The complexity and functionalization of standard visible light sensors can be significantly improved through the integration of miniaturized spectrometers that can detect from the visible to the SWIR region of the spectrum. The future being imagined by researchers at Fraunhofer is a spectrometer weighing just 1 gram and costing a single dollar. Miniaturized spectrometers are expected to deliver inexpensive solutions to improve autonomous efficiency, particularly within industrial imaging and inspection as well as consumer electronics.
 
IDTechEx has 20 years of expertise covering emerging technologies, including image sensors, thin film materials, and semiconductors. Our analysts have closely followed the latest developments in relevant markets, interviewed key players within the industry, attended conferences, and delivered consulting projects on the field. This report examines the current status and latest trends in technology performance, supply chain, manufacturing know-how, and application development progress. It also identifies the key challenges, competition and innovation opportunities within the image sensor market.
 
Key aspects
This report provides the following information:
  • Detailed analysis of multiple emerging image sensing technologies.
  • Highly granular 10-year market forecasts, split by technology and subsequently by application. This includes over 40 individual forecast categories.
  • Technological/commercial readiness assessments, split by technology and application.
  • Commercial motivation for developing and adopting each of the emerging image sensing technologies.
  • Multiple application case studies for each image sensing technology.
  • SWOT analysis of each image sensing technology.
  • Overview of the key players within each technology category.
  • Over 25 company profiles, the majority based on recent primary interviews. These include a discussion of current status, technology, potential markets and business model, along with company financial information (where disclosed) and our SWOT analysis.
  • Selected highlights from academic research relevant to emerging image sensor technologies.

 



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Table of Contents

1. EXECUTIVE SUMMARY
1.1. Motivation for emerging image sensor technologies
1.2. Report structure
1.3. Emerging image sensor technologies included in the report
1.4. Comparison with IDTechEx's previous Emerging Image Sensors report
1.5. Conventional image sensors: Market overview
1.6. Opportunities for SWIR image sensors
1.7. Autonomous vehicles will need machine vision
1.8. Application readiness level of SWIR detectors
1.9. Prospects for QD/OPD-on-CMOS detectors
1.10. Challenges for QD-Si technology for SWIR imaging
1.11. Future of pulse oximetry could come in the form of flexible skin patches with thin film photodetectors
1.12. Applications for hyperspectral imaging
1.13. Event-based vision promises reduced data processing and increased dynamic range
1.14. Emerging flexible x-ray sensors - Lightweight and low-cost
1.15. Miniaturised spectrometers targeting a wide range of sectors
1.16. The emergence of quantum image sensing
1.17. Emerging image sensors: Key players overview
1.18. Emerging image sensors: Key players overview (II)
1.19. 10-year market forecast for emerging image sensor technologies
1.20. 10-year market forecast for emerging image sensor technologies (by volume)
1.21. 10-year market forecast for emerging image sensor technologies (by volume, data table)
1.22. 10-year market forecast for emerging image sensor technologies (by market value)
1.23. 10-year market forecast for emerging image sensor technologies (by market value, data table)
1.24. Key conclusions for emerging image sensors
2. INTRODUCTION
2.1. Motivation for emerging image sensor technologies
2.2. What is a sensor?
2.3. Sensor value chain example: Digital camera
2.4. Introduction to photodetectors
2.5. Working principle of an image sensor
2.6. Quantifying photodetector and image sensor performance
2.7. Extracting as much information as possible from light
2.8. Global autonomous car market
2.9. How many cameras needed in different automotive autonomy levels
2.10. Increasing usage of drones provides extensive market for emerging image sensors
2.11. Emerging image sensors required for drones
2.12. Industrial imaging to benefit from integrated hyperspectral "package" solutions
2.13. Advanced sensors expected to target consumer electronics
3. MARKET FORECASTS
3.1. Market forecast methodology
3.2. Parametrizing forecast curves
3.3. Determining total addressable markets
3.4. Determining revenues
3.5. 10-year short-wave infra-red (SWIR) image sensors market forecast: By volume
3.6. 10-year short-wave infra-red (SWIR) image sensors market forecast: by market value
3.7. 10-year short-wave infra-red (SWIR) image sensors market volume forecast data table
3.8. 10-year short-wave infra-red (SWIR) image sensors market value forecast data table
3.9. 10-year hybrid OPD-on-CMOS image sensors market forecast: by volume
3.10. 10-year hybrid OPD-on-CMOS image sensors market forecast: by market value
3.11. 10-year hybrid OPD-on-CMOS image sensors market volume forecasts (data table)
3.12. 10-year hybrid OPD-on-CMOS image sensors market value forecasts (data table)
3.13. 10-year hybrid QD-on-CMOS image sensors market forecast: by volume without consumer electronics
3.14. 10-year hybrid QD-on-CMOS image sensors market forecast: by market value without consumer electronics
3.15. 10-year hybrid QD-on-CMOS image sensors market volume forecasts (data tables) without consumer electronics
3.16. 10-year hybrid QD-on-CMOS image sensors market value forecasts (data tables) without consumer electronics
3.17. 10-year hybrid QD-on-CMOS image sensors market forecast: by volume including consumer electronics
3.18. 10-year hybrid QD-on-CMOS image sensors market forecast: by value including consumer electronics
3.19. 10-year hybrid QD-on-CMOS image sensors market volume forecasts (data tables) with consumer electronics
3.20. 10-year hybrid QD-on-CMOS image sensors market value forecasts (data tables) with consumer electronics
3.21. 10-year thin film organic and perovskite photodetectors (OPDs and PPDs) market forecast: by volume
3.22. 10-year thin film organic and perovskite photodetectors (OPDs and PPDs) market forecast: by value
3.23. 10-year thin film organic and perovskite photodetectors (OPDs and PPDs) market volume forecasts (data table)
3.24. 10-year thin film organic and perovskite photodetectors (OPDs and PPDs) market value forecasts (data table)
3.25. 10-year hyperspectral imaging market forecast: by volume
3.26. 10-year hyperspectral imaging market forecast: by value
3.27. 10-year hyperspectral imaging market volume forecasts (data table)
3.28. 10-year hyperspectral imaging market value forecasts (data table)
3.29. 10-year event-based vision market forecast: by volume
3.30. 10-year event-based vision market forecast: by value
3.31. 10-year event-based vision market volume forecasts (data tables)
3.32. 10-year event-based vision market value forecasts (data tables)
3.33. 10-year wavefront imaging market forecast: by volume
3.34. 10-year wavefront imaging market forecast: by value
3.35. 10-year wavefront imaging market volume forecasts (data table)
3.36. 10-year wavefront imaging market value forecasts (data table)
3.37. 10-year flexible x-ray image sensors market forecast: by volume
3.38. 10-year flexible x-ray image sensors market forecast: by value
3.39. 10-year miniaturized spectrometers market forecast: by volume
3.40. 10-year miniaturized spectrometers market forecast: by market value
3.41. 10-year flexible miniaturized spectrometers market volume forecasts (data table)
3.42. 10-year flexible miniaturized spectrometers market value forecasts (data table)
4. BRIEF OVERVIEW OF ESTABLISHED VISIBLE RANGE IMAGE SENSORS (CCD AND CMOS)
4.1. Conventional image sensors: Market overview
4.2. Sensor architectures: Front and backside illumination
4.3. Key components of an image sensor
4.4. Process flow for back-side-illuminated CMOS image sensors
4.5. Comparing CMOS and CCD image sensors
4.6. Image quality
4.7. CCD & CMOS image sensors
4.8. What is measured by an image sensor
4.9. Benefits of global rather than rolling shutters
4.10. Dynamic photodiodes with tuneable sensitivity
5. SHORT WAVE INFRARED (SWIR) IMAGE SENSORS
5.1. Introduction
5.1.1. Electromagnetic spectrum
5.1.2. Short-wave infrared spectrum
5.1.3. Value propositions of SWIR imaging
5.1.4. SWIR imaging reduces light scattering
5.1.5. Material choices for infrared sensors
5.1.6. Introduction to SWIR detection technologies
5.1.7. SWIR imaging: Incumbent and emerging technology options
5.1.8. Detectivity benchmarking of emerging image sensor technologies 1
5.1.9. Detectivity benchmarking of emerging image sensor technologies 2
5.1.10. Technology comparison of various image sensor technologies for SWIR imaging
5.2. Applications for SWIR Imaging
5.2.1. Applications for SWIR imaging
5.2.2. SWIR imaging for silicon wafer inspection
5.2.3. SWIR imaging for water content identifying
5.2.4. SWIR imaging for ADAS and autonomous vehicles
5.2.5. SWIR imaging for r

 

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