The global computational photography market is predicted to reach USD 15.92 billion in 2024 and USD 43.03 billion by 2029, growing at a CAGR of 22% during the forecast period.
Computational photography mainly refers to capturing digital images and applying several processing techniques in place of optical processes. Computational photography is done using digital cameras, especially smartphones, and includes automatic settings to improve shooting capabilities. It uses image processing algorithms to enhance images by reducing motion blur and adding simulated depth of field and color refinement, contrast, and light range. High Dynamic Range (HDR) imaging with panoramas is a popular computational photography that optimally combines information from multiple images exposed differently from overlaid and underexposed images. The use of computational photography has increased due to its advantages as it provides better machine vision systems at lower cost and improves images with better colors, better contrast, and better lighting techniques. For example, in 2018, Xiaomi launched the Xiaomi Mi 8 smartphone, which provides computer photographs. This smartphone uses machine learning with artificial intelligence techniques to enhance photos and provides a 20-megapixel shutter button that lets you take selfies with AI.
In the same way that smartphone cameras rely on computational photography to adjust images despite the small physical lenses of a smartphone camera, it can enhance images of visually impaired people with Augmented Reality (AR). In July 2019, Nvidia Corporation launched its prescription smart glasses that make use of AR reality to enhance a person's vision.
The increasing adoption of the Image Fusion technique to achieve high-quality images is driving the market. As image fusion techniques have developed rapidly in various types of applications in recent years, methods that can objectively, systematically, and quantitatively assess or assess the performance of different fusion technologies have been recognized as an urgent need. The advancements in the night color image are becoming significant in both computational photography and computer vision.
Mobile phone photography has expanded drastically from VGA cameras to higher-megapixel cameras. In recent years, smartphone camera technology has grown exponentially. Currently, smartphone manufacturers are talking about artificial intelligence (AI) and machine learning that will be implemented on their phones. According to Morgan Stanley, with the increase in the sales reach of the Android smartphone in the coming years, the deployment of digital photography in more brands is highly predictable.
Qualcomm Spectra ISP technology integrated digital photography into smartphones to take photos to the next level. The next round of computational photography added to machine learning will be visible in both photos and videos.
At the Snapdragon Tech Summit in 2019, Qualcomm demonstrated a Snapdragon 865 AI-compatible "image segmentation" feature with Morpho software.
Google Pixel 4 is the latest example of the implementation of computational photography in smartphone cameras. Google has introduced Pixel 4 and Pixel 4 XL, a new version of its popular smartphone, available in two screen sizes. While the devices include new hardware features such as an additional camera lens and infrared facial scanner to unlock the phone, Google has emphasized the use of phones by computer photography, which automatically deals with images to make them. More professionals.
These new features provide a way to photograph the night sky and capture images of the stars. By adding the additional lens, Google created a software feature called Super Res Zoom, which allows users to get closer to images without losing much detail. Most important is the functionality of Android Night Sight in computational photography.
The growing trends in the exchange of videos and images, along with the increasing use of social networks, are the main growth engines of the global computational photography market. Today's people tend to stay connected globally through social media apps like WhatsApp and Facebook. This has led to the integration of high-end cameras in smartphones. Additionally, smartphone penetration has increased globally, further driving the adoption of high-end smartphones with advanced cameras.
Rapid advances in technology have also led to many developments in image processing. People can capture and generate high-quality images, manipulate them using various applications, and share them at their convenience. With increasing disposable income and improving living standards, the digital photography market is expected to grow exponentially in the near future.
However, less awareness and high costs related to computer photography techniques can slow the growth of the global computational photography market in underdeveloped regions.
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REPORT METRIC |
DETAILS |
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Market Size Available |
2023 to 2029 |
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Base Year |
2023 |
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Forecast Period |
2024 to 2029 |
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CAGR |
22% |
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Segments Covered |
By Application and Region |
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Various Analyses Covered |
Global, Regional & Country Level Analysis, Segment-Level Analysis, DROC, PESTLE Analysis, Porter’s Five Forces Analysis, Competitive Landscape, Analyst Overview on Investment Opportunities |
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Regions Covered |
North America, Europe, APAC, Latin America, Middle East & Africa |
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Market Leaders Profiled |
Apple Inc., Google, Qualcomm Technologies, NVIDIA Corporation, Light, Algolux, Movidius, ALMALENCE INC. and Others. |
According to the application, the global market for computational photography can be segmented into smartphone cameras, independent cameras, and machine vision. Of these, smartphones account for a significant portion of the global market and are likely to witness considerable CAGR in the coming years.
In the developed economies of North America and Western Europe, emphasis is placed on innovations due to increased disposable income and the strong presence of suppliers. As a result, North America has the largest revenue contribution to the computational photography market. The APAC region is also expected to experience a significant growth rate for the worldwide market due to the large number of smartphone manufacturers in the region.
The key vendors in the global Computational Photography market are Apple Inc., Google, Qualcomm Technologies, Inc., NVIDIA Corporation, Light, Algolux, Movidius, ALMALENCE INC., and Pelican Imaging.
In April 2020, Xiaomi announced the integration of a 144-megapixel camera phone, whereas the predecessors of these two phones, the Mi 10 Pro and Mi CC9 Pro, had 108-megapixel cameras. Phones use computational photography and prioritize even more to improve their computational photography capabilities.
By Application
By Region
Frequently Asked Questions
Key drivers include the proliferation of smartphones with advanced camera systems, the rise of social media and the demand for high-quality images, advancements in AI and machine learning, and the integration of computational photography technologies in various consumer and professional devices.
AI is a major influencer in the computational photography market. It enhances image quality through machine learning algorithms that improve autofocus, exposure, color correction, and noise reduction. AI also enables new features like scene recognition, real-time image processing, and improved low-light photography.
The market is expected to see continued growth, driven by further advancements in AI and machine learning, increasing demand for AR and VR applications, and the integration of computational photography in new industries such as healthcare and automotive. Improved hardware capabilities and more affordable devices will also contribute to market expansion.
Computational photography has significantly disrupted traditional photography industries by democratizing high-quality imaging. It has led to a decline in standalone camera sales as smartphones with advanced computational capabilities become more prevalent. However, it has also spurred innovation, pushing traditional camera manufacturers to incorporate more sophisticated software and AI features into their products.
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