Like the human eye, a camera relies on various parts (lens, filters, and electronics) to provide visual clarity, color, and depth. In smartphone cameras, one of the key components comparable to the human eye's retina is called a CMOS image sensor, or CIS.
The original purpose of CIS technology was to optimize image quality for human viewing. Now, CIS technology is being improved for a new purpose—enhancing human vision. It is being used as a sensor to collect digital image information, which provides data for emerging artificial intelligence (AI) applications. From screening for defects in the manufacturing process to detecting objects in dark environments, the technology has many new uses.
As photo capabilities on mobile devices become more powerful and competitive, it is expected that the technology will continue to improve and drive further innovation.
In 2023, the global image sensor market reached $23.2 billion.
According to a 2018 report by Research and Markets, the global image sensor market is projected to grow by 6.2% to reach $23.2 billion by 2023.
In most cases, growth is primarily attributed to improvements in image sensor performance, but other factors are also at play. Smartphone manufacturers have viewed camera innovation as a way to differentiate their devices from competitors in a saturated market. New and diverse camera features, such as optical zoom, require advanced sensor technology. The development of low-power and compact image sensors, as well as the increasing use of image sensing devices in biometric applications, have also contributed. The trend of using multiple cameras in mobile devices has become a driving factor.
In smartphone cameras, image quality is often closely related to the image sensor (CIS), as its performance affects key factors such as resolution, sensitivity, and signal-to-noise ratio (SNR). This has also led to the emergence of new product applications and improved the performance of imaging devices. As a result, the image quality of smartphone camera CIS has surpassed that of compact cameras and is increasingly closing the gap with DSLR cameras.
Innovation and Development of Image Sensor Technology
Initially, the goal of CIS technology was to optimize image quality for the human eye. With technological advancements, the focus shifted to achieving image quality optimized for machine algorithms. However, the diffraction limit restricts the ability to miniaturize CIS pixels.
As a result, the company has improved the integration level of CIS pixels by continuously developing equipment and processing technologies, as well as by developing image signal processing or ISP technologies to support various application areas. This is a gradual transformation.
In the first phase, pixel engineers focused on compensating for the inevitable loss of sensitivity due to the reduction in pixel size, and developed many innovative technologies, including on-chip lenses (or microlenses), deep photodiodes with thicker silicon, and back-illumination technology.
With pixel sizes reaching approximately 1 micrometer, the second phase began to focus more on reducing crosstalk. During this period, new technologies were developed to suppress optical and electrical crosstalk, such as metal lattice structures in color filter layers and deep trench isolation processes for Si photodiodes. Through these innovations, the CIS platform is expected to evolve into an information sensor that supports advanced additional functions, going beyond simply improving image quality.
Another driving force behind this innovation is the emergence of stacked sensor technology. Because conventional sensors have a structure where pixels and circuitry are implemented on the same substrate, the dark areas must be reduced to decrease the size of the CIS (CMOS Image Sensor). Therefore, only the basic functions of analog/digital circuitry are implemented, and the addition of circuitry for additional functions is very limited.
Leveraging advanced semiconductor processes, SK Hynix's stacked sensors have enabled the embedding of simple AI hardware engines into the ISP on the underlying substrate. Simultaneously, new machine learning-based technologies, such as super-resolution, color reproduction, facial recognition, and object recognition, are under development.
Main applications of image sensors
These new chips will play a role in multiple fields, and some innovative products have already begun to hit the market.
Sony recently announced two models of intelligent vision sensors, the world's first image sensors equipped with AI processing capabilities for cloud services. These products expand opportunities for developing AI-enabled cameras, enabling a variety of applications in the retail and industrial equipment sectors, and helping to build optimal systems linked to the cloud.
For example, cameras equipped with these sensors installed at facility entrances can count the number of visitors entering the facility. When installed on retail shelves, it can detect stock shortages. Mounted on the ceiling, it can be used to heat up a map of visitors to identify areas where people congregate most. Because it uses machine learning-based ISP technology to extract and classify various features from input images, CIS will become a key component of information sensors that collect various data points about images, location, distance, and other biometric information.
This becomes especially important when applied to autonomous vehicles, which use at least ten cameras to detect their surroundings. To improve accuracy, various requirements must be met, such as high-resolution support for distinguishing objects at distances, HDR support for recognizing objects even in dark environments, and preprocessing of the ISP to reduce the computational load on the processor.
In the field of security, one function requires compressing and encrypting image signals from the CIS's built-in ISP before transmitting them to an external processor. Sending unencrypted image signals externally increases the likelihood of security vulnerabilities and information leaks. Therefore, the encryption functionality within the CIS is crucial.
Smartphone apps dominate the CIS market share, but many other applications are expected to emerge as CIS growth drivers, particularly with the development and evolution of machine vision applications. These emerging opportunities are propelling the technology from mobile imaging into other growth areas, and we may see a shift from using vision for imaging to using vision for sensing and other interactive applications.
Looking ahead, CIS will be used in a variety of applications, including smartphone cameras, which will help create economic and social value, making it an important component of information sensors in the future.
