The global computational photography market was estimated to be worth $ 10.7 billion in 2020 and is projected to reach $ 29.0 billion by 2025, with a compound annual growth rate of 22.0% during the outlook period 2020 to 2025.
Computational photography mainly refers to the capturing of digital images and applying several processing techniques in the place of optical processes. Computational photography is done using digital cameras and especially smartphones that include automatic settings to improve shooting capabilities. It uses image processing algorithms to enhance images by reducing motion blur, and also adds simulated depth of field and color refinement, contrast, and light range. High Dynamic Range (HDR) imaging with panoramas is the 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, 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 provide 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 the vision of a person.
The increasing adoption of Image Fusion technique to achieve high quality image is driving the market. As image fusion techniques have developed rapidly in various types of applications in recent years, methods which 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 is becoming significant in both computational photography and computer vision.
Recent Developments:
April 2020: Xiaomi announced the integration of a 144-megapixel camera phone, where the predecessors of these two phones, 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.
In October 2015, Google acquired Digisfera, a start-up specializing in panoramic images. This acquisition aimed to improve the customer experience using Street View technology developed by Google for Google Maps, using 360-degree photography.
With the effect of the COVID-19 impact, the production of smartphones for the first half of 2020 is expected to decrease significantly. The coronavirus outbreak poses a prominent threat to the mobile phone business, with major impact on manufacturing and overall sales. Globally, semiconductor revenue is expected to decline by nearly 2-3% in 2020. In addition, it has disrupted the supply chain with some smartphone brands such as Sony, Samsung, which announced the Snapdragon 865 AI integration enabled by Qualcomm (it has a camera architecture that should advance computational photography). This causes a delay in production, as it is currently unpredictable when the pandemic is overcome.
Market Growth and Trends:
Android smartphone to witness significant market growth in the coming years
Market Drivers and Limitations:
The growing trends in the exchange of videos and images along with the increasing use of social networks are the main growth engine of the global computational photography market. Today's people tend to stay connected globally, through social media apps, like What Sapp, Facebook. All this has led to the integration of high-end cameras in smart phones. 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 terms of image processing in which 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.
Market Segmentation:
The global digital photography market is segmented by application and region.
According to the application, the global market for computational photography can be segmented into smartphone cameras, independent cameras, and machine vision. Of these, smartphones accounted for a significant portion of the global market and are likely to witness considerable CAGR in the coming years.
Geographical Analysis:
Regionally, the global computational photography market can be segmented into North America, Latin America, Western Europe, Eastern Europe, the Middle East, and Africa (MEA), and Asia-Pacific.
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.
Key players in the market:
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.
1. Introduction
1.1 Market Definition
1.2 Scope of the report
1.3 Study Assumptions
1.4 Base Currency, Base Year and Forecast Periods
2. Research Methodology
2.1 Analysis Design
2.2 Research Phases
2.2.1 Secondary Research
2.2.2 Primary Research
2.2.3 Data Modelling
2.2.4 Expert Validation
2.3 Study Timeline
3. Report Overview
3.1 Executive Summary
3.2 Key Inferencees
4. Market Dynamics
4.1 Impact Analysis
4.1.1 Drivers
4.1.2 Restaints
4.1.3 Opportunities
4.2 Regulatory Environment
4.3 Technology Timeline & Recent Trends
5. Competitor Benchmarking Analysis
5.1 Key Player Benchmarking
5.1.1 Market share analysis
5.1.2 Products/Service
5.1.3 Regional Presence
5.2 Mergers & Acquistion Landscape
5.3 Joint Ventures & Collaborations
6. Market Segmentation
6.1 Computational Photography Market, By Application
6.1.1 Smartphones Cameras
6.1.2 Machine Vision
6.1.3 Independent Cameras
6.1.4 Market Size Estimations & Forecasts (2019-2024)
6.1.5 Y-o-Y Growth Rate Analysis
6.1.6 Market Attractiveness Index
7. Geographical Landscape
7.1 Global Identity Governance and Administration Market, by Region
7.2 North America - Market Analysis (2018 - 2024)
7.2.1 By Country
7.2.1.1 USA
7.2.1.2 Canada
7.2.2 By Application
7.3 Europe
7.3.1 By Country
7.3.1.1 UK
7.3.1.2 France
7.3.1.3 Germany
7.3.1.4 Spain
7.3.1.5 Italy
7.3.1.6 Rest of Europe
7.3.2 By Application
7.4 Asia Pacific
7.4.1 By Country
7.4.1.1 China
7.4.1.2 India
7.4.1.3 Japan
7.4.1.4 South Korea
7.4.1.5 South East Asia
7.4.1.6 Australia & NZ
7.4.1.7 Rest of Asia-Pacific
7.4.2 By Application
7.5 Latin America
7.5.1 By Country
7.5.1.1 Brazil
7.5.1.2 Argentina
7.5.1.3 Mexico
7.5.1.4 Rest of Latin America
7.5.2 By Application
7.6 Middle East and Africa
7.6.1 By Country
7.6.1.1 Middle East
7.6.1.2 Africa
7.6.2 By Application
8. Key Player Analysis
8.1 Apple Inc
8.1.1 Business Description
8.1.2 Products/Service
8.1.3 Financials
8.1.4 SWOT Analysis
8.1.5 Recent Developments
8.1.6 Analyst Overview
8.2 Google
8.3 Qualcomm Technologies
8.4 Nvidia Corporation
8.5 Light
8.6 Algolux
8.7 Movidius
8.8 Almalence Inc
8.9 Pelican Imaging
9. Market Outlook & Investment Opportunities
Appendix
List of Tables
List of Figures
