Dublin, May 03, 2022 (GLOBE NEWSWIRE) — The “Computational Photography Market – Forecasts from 2022 to 2027” report has been added to ResearchAndMarkets.com’s offering.
The global computational photography market was valued at US$6.618 billion in 2020 and is expected to grow at a CAGR of 21.61% over the forecast period to reach a total market size of US$26.033 billion by 2027.
Camera settings can be automated through computational photography allowing for better point-and-shoot photography on digital cameras and particularly smartphones. The hardware is used for advanced computation to facilitate computational photography. By compressing, expanding, and mosaicking an image, this software system enhances and expands the capabilities of computational photography.
The North American machine vision market, which includes smart cameras, grew from USD1.8 billion in sales in 2010 to USD 2.07 billion in September 2019 according to AIA (Association for Advancing Automation). In addition to being driven by the need for better product inspection and quality control in manufacturing, this growth is also fuelled by an increasing need for more intelligent collaborative robots in the industry. The computational photography market is being driven by the above factors. Furthermore, mobile devices are becoming increasing capable of capturing high-quality images as computing technology advances. In the most recent development, for example, Xiaomi has shared information about the camera department of its next-generation flagship smartphone Mi 11. As a result of this announcement, Xiaomi Mi 11 will come with support for computational photography, a technique for capturing and processing images that employ digital computation instead of optical techniques.
Computation photography market is also being driven by the increasing adoption of image fusion techniques to achieve high-quality images. Recently, fusion techniques have gained popularity in various types of applications, making the need for objective, systematic, and quantitative methods to assess or evaluate the performance of these technologies urgently necessary.
Increasing use of Smartphones
Over the past decade, smartphones have witnessed improved picture-taking capabilities, with the cameras evolving exponentially in recent years. Mobile phone manufacturers are currently making announcements about integrating Artificial Intelligence (AI) and machine learning on their devices. The Qualcomm Spectra ISP technology in conjunction with computational photography capabilities can take images taken on smartphones to an entirely new level.
During the Snapdragon Tech Summit in 2019, Qualcomm unveiled an AI-powered “image segmentation” feature powered by Morpho software on its Snapdragon 865 processor. Major brands have come up with ways to make pictures look better with their smartphones, whether they are flagships from Huawei and Google or affordable smartphones from Xiaomi and Oppo. Xiaomi announced in April 2020 that it would incorporate a 144-megapixel camera into the Mi 10 Pro and Mi CC9 Pro, which had, respectively, 108-megapixel cameras. Computational photography is bein used in these phones, and its features are constantly being improved.
Google’s Pixel 4 uses computational photography in order to develop smartphones with cameras that are cutting-edge. With computational photography, the phone’s images are automatically enhanced to appear more professional. Among the most notable features in computational photography is Android’s Night Sight. This new feature provides a method for photographing the night sky and capturing images of stars. It is also predicted that the triple camera will become a popular feature for smartphone photography in the future. 2021 will see the launch of the Google Pixel 5XL and Google Pixel 5. The next iteration of Google Photos will leverage triple cameras to click on amazing images through machine learning and artificial intelligence thus boosting the market for computational photography.
Microsoft announced the Surface Duo smartphone in April 2020. The Surface Duo will run on an Android operating system, whatever comes after the release of Android 10. Computational photography algorithms will be used to process the images generated by the device’s CMOS multi-sensor, 3D, IR camera.
The market growth of computational camera modules is however held back by high maintenance and manufacturing costs. The price of mobile phones rises as smartphone vendors strive to improve image quality.
COVID-19 Impact on Computational Photography Market:
For the first half of 2020, the number of smartphones produced drastically reduced due to the COVID-19 effect. The Qualcomm Snapdragon 865 AI-enabled phone brand was announced by some smartphone manufacturers, including Sony and Samsung, who will be using its camera architecture to advance computational photography. This caused the delay in production since the state of the pandemic madeit unclear regarding the demand. The world has been experiencing a decline in demand for analog semiconductors due to the stagnation of new projects. This market has been temporarily affected by COVID-19 since the supply chain chain was affected. A positive change in the economic environment will lead to an increase in production, restoring of supply chains, and increasing demand for computational photography solutions.
Key Topics Covered:
2. Research Methodology
3. Executive Summary
4. Market Dynamics
4.1. Market Drivers
4.2. Market Restraints
4.3. Porters Five Forces Analysis
4.3.1. Bargaining Power of Suppliers
4.3.2. Bargaining Power of Buyers
4.3.3. The threat of New Entrants
4.3.4. Threat of Substitutes
4.3.5. Competitive Rivalry in the Industry
4.4. Industry Value Chain Analysis
5. Computational Photography Market Analysis, By Application
5.3. Smart Phones
5.4. Machine Vision
6. Computational Photography Market Analysis, By Geography
6.2. North America
6.2.1. United States
6.3. South America
6.5. Middle East and Africa
6.5.1. Saudi Arabia
6.6. Asia Pacific
7. Competitive Environment and Analysis
7.1. Major Players and Strategy Analysis
7.2. Emerging Players and Market Lucrativenessness
7.3. Mergers, Acquisitions, Agreements, and Collaborations
7.4. Vendor Competitiveness Matrix
8. Company Profiles
8.3. Microsoft Corporation
8.5. Facebook Inc.
8.6. Apple Inc.
8.7. Corephotonics Ltd.
8.8. Micron Technology
8.9. Guandong Oppo Mobile Telecommunications Corp.
8.10. Photogram AI
For more information about this report visit https://www.researchandmarkets.com/r/ots0iq