Report Scope & Overview:
Computational Photography Market size was valued at USD 19.58 Bn in 2022 and is expected to reach USD 106.39 Bn by 2030, and grow at a CAGR of 23.56% over the forecast period 2023-2030.
Computational photography is prevalent in digital cameras, especially smartphones, where it automates various settings to enable better point-and-shoot technology. Computational photography improves photographs by minimizing motion blur, introducing artificial depth of field, and boosting color, contrast, and light range using image processing techniques. Computing imaging makes use of the hardware's powerful computational capabilities. By compressing, enlarging, and mosaicking a picture, these software solutions enhance and extend the capabilities of computational photography-based devices. As computational photography technology progresses, cellphones enable non-professional photographers to produce higher-quality photographs.
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The market is being driven by the increasing use of the Image Fusion Technique to create high-quality images. Since image fusion techniques have advanced rapidly in a variety of applications in recent years, methods for objectively, systematically, and statistically assessing or evaluating the performance of various fusion technologies have been identified as an essential demand. The improvement of night color images is critical in both computational photography and computer vision.
It can successfully boost the scene's visibility and strangeness. Furthermore, at night, artificial lighting light spreads unevenly, lowering the quality of monitoring images and increasing the complexity of surveillance. As a result, night color picture enhancement can help boost video surveillance.
Government and commercial investments in electronic documents are expanding quickly.
Rapid Growth in the Demand for High-Resolution Still Cameras.
Computational Photography is becoming more popular in smartphone cameras.
Computational Camera Modules Have Expensive Maintenance and Manufacturing Costs.
Image Fusion Technique Is Becoming More Popular for Producing High-Quality Images.
Displays with 4k resolution are becoming more popular.
In Machine Vision, there is an increasing demand for high-resolution computational cameras.
Growing Interest in Image Sensor Chip Miniaturization.
IMPACT OF COVID-19:
The COVID-19 epidemic has had a severe influence on the global computational photography sector. New projects throughout the world have stopped, resulting in a drop in demand for analog semiconductors. As workers stayed at home, multinational factories struggled to incorporate new computational photographic equipment, disrupting global supply chains. COVID-19's influence on this market is very temporary because only the production and supply chain are halted. Production, supply networks, and demand for computational photography will steadily expand as the situation improves. This COVID-19 shutdown would assist businesses in considering more innovative ways to improve efficiency.
The adoption of AI-based sophisticated cameras and the rising need for arrays of cameras in a single product are driving the market expansion of camera modules. Each computational camera's hardware and software are often tailored to create a certain sort of image. The picture is optically encoded. The computational module contains an optics model that it utilizes to interpret the acquired picture and create a new sort of image that might help a vision system.
The increased sales of smartphones equipped with powerful cameras and artificial intelligence capabilities are driving the computational photography industry. The market for smartphone-based computational cameras is changing dramatically. Computational cameras have a significant influence on the smartphone industry. Smartphones are now incorporating computational photography.
The rise of smartphone cameras that employ single- and dual-lens camera modules for sophisticated imaging is driving demand for these cameras. With multiple lens cameras, manufacturers have been able to incorporate additional features like as zoom, improved HDR, portrait settings, 3D, and low-light shooting. New generations of smartphones with strong dual back cameras have just been released.
Computational photography cameras can be used to capture photographs of a specific item from which an automated model of the scene can be built. With the use of this technology, a wide variety of conceivable adjustments, including scene geometry and textures, may be examined interactively and evaluated on-set. With developments in computer vision technology, it is now feasible to record 3D pictures using a variety of sensors and extract depth information in the process. Mixed reality is the next development in human, computer, and environment interaction, unlocking previously unimaginable possibilities. With the use of sophisticated imagery, computational photography is expected to improve consumer experience when integrated with virtual reality.
KEY MARKET SEGMENTS:
On The Basis of Offering
On The Basis of Type
Single- and Dual-Lens Camera
16- Lens Camera
On The Basis of Product
Machine Vision Cameras
On The Basis of Application
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Because of rising disposable money, North America dominates the computational photography business. Furthermore, the presence of significant key players will drive the region's computational photography market growth throughout the projection period. The frenzy and anticipation for the new iPhone in the United States stifle the progress of computational photography. Deep Fusion selects the most detailed short-exposure picture and blends it with the long synthetic exposure. Deep Fusion, unlike Smart HDR, blends these two frames and processes noise differently than Smart HDR. Because of the increased number of smartphone manufacturers, Asia-Pacific is expected to see considerable development in the computational photography industry.
Rest of Europe
Rest of Asia-Pacific
The Middle East & Africa
Rest of Middle East & Africa
Rest of Latin America
Qualcomm -Company Financial Analysis
|Market Size in 2022||US$ 19.58 Billion|
|Market Size by 2030||US$ 106.39 Billion|
|CAGR||CAGR of 23.56% From 2023 to 2030|
|Report Scope & Coverage||Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook|
|Key Segments||• By Offering (Camera Modules and Software)
• By Type (Single- and Dual-Lens Camera, 16- Lens Camera, Others)
• By Product (Smartphone Cameras, Standalone Cameras, and Machine Vision Cameras),
• By Application (3D Imaging, Virtual Reality, Augmented Reality, and Mixed Reality)
|Regional Analysis/Coverage||North America (USA, Canada, Mexico), Europe
(Germany, UK, France, Italy, Spain, Netherlands,
Rest of Europe), Asia-Pacific (Japan, South Korea,
China, India, Australia, Rest of Asia-Pacific), The
Middle East & Africa (Israel, UAE, South Africa,
Rest of Middle East & Africa), Latin America (Brazil, Argentina, Rest of Latin America)
|Company Profiles||Apple, Samsung, Nvidia, Qualcomm, Adobe, Nikon, Sony, LG, Light, Canon|
|KEY DRIVERS||• Government and commercial investments in electronic documents are expanding quickly.
• Rapid Growth in the Demand for High-Resolution Still Cameras.
• Computational Photography is becoming more popular in smartphone cameras.
|Restraints||• Computational Camera Modules Have Expensive Maintenance and Manufacturing Costs.|
Ans: - The Computational Photography Market size was valued at USD 19.58 Bn in 2022.
Ans: - Growing Interest in Image Sensor Chip Miniaturization.
Ans: - The Computational Photography Market is to grow at a CAGR of 23.56% over the forecast period 2023-2030.
Ans: - The major key players are Apple, Samsung, Nvidia, Qualcomm, Adobe, Nikon, Sony, LG, Light, Canon.
Ans: - The study includes a comprehensive analysis of Computational Photography Market trends, as well as present and future market forecasts. DROC analysis, as well as impact analysis for the projected period. Porter's five forces analysis aids in the study of buyer and supplier potential as well as the competitive landscape etc.
Table of Contents
1.1 Market Definition
1.3 Research Assumptions
2. Research Methodology
3. Market Dynamics
4. Impact Analysis
4.1 COVID-19 Impact Analysis
4.2 Impact of Ukraine- Russia war
4.3 Impact of ongoing Recession
4.3.2 Impact on major economies
126.96.36.199 United Kingdom
188.8.131.52 South Korea
184.108.40.206 Rest of the World
5. Value Chain Analysis
6. Porter’s 5 forces model
7. PEST Analysis
8. Computational Photography Market Segmentation, by Offering
8.1 Camera Modules
9. Computational Photography Market Segmentation, by Type
9.1 Single- and Dual-Lens Camera
9.2 16- Lens Camera
10. Computational Photography Market Segmentation, by Product
10.1 Smartphone Cameras
10.2 Standalone Cameras
10.3 Machine Vision Cameras
11. Computational Photography Market Segmentation, by Application
11.1 3D Imaging
11.2 Virtual Reality
11.3 Augmented Reality
11.4 Mixed Reality
12. Regional Analysis
12.2 North America
12.3.6 The Netherlands
12.3.7 Rest of Europe
12.4.2 South Korea
12.4.6 Rest of Asia-Pacific
12.5 The Middle East & Africa
12.5.3 South Africa
12.6 Latin America
12.6.3 Rest of Latin America
13. Company Profiles
13.1.2 Products/ Services Offered
13.1.3 SWOT Analysis
13.1.4 The SNS view
14. Competitive Landscape
14.1 Competitive Benchmarking
14.2 Market Share Analysis
14.3 Recent Developments
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