The technology industry continues to be a hotbed of patent innovation. Activity is driven by the increasing demand for high-quality images in various sectors including healthcare, gaming, and photography, along with continuous advancements in artificial intelligence (AI) technology and computing capabilities, and growing importance of technologies such as CNNs for intricate feature extraction and image enhancement, as well as adaptive filtering techniques to refine and smoothen visual data, collectively driving the evolution of AI in image smoothing. In the last three years alone, there have been over 4.1 million patents filed and granted in the technology industry, according to GlobalData’s report on Artificial intelligence in technology: image smoothing. Buy the report here.
However, not all innovations are equal and nor do they follow a constant upward trend. Instead, their evolution takes the form of an S-shaped curve that reflects their typical lifecycle from early emergence to accelerating adoption, before finally stabilizing and reaching maturity.
Identifying where a particular innovation is on this journey, especially those that are in the emerging and accelerating stages, is essential for understanding their current level of adoption and the likely future trajectory and impact they will have.
190+ innovations will shape the technology industry
According to GlobalData’s Technology Foresights, which plots the S-curve for the technology industry using innovation intensity models built on over 1.5 million patents, there are 190+ innovation areas that will shape the future of the industry.
Within the emerging innovation stage, GenAI for design, finite element simulation, and deep reinforcement learning are disruptive technologies that are in the early stages of application and should be tracked closely. AI in EHR, intelligent predictive maintenance, and forward inferencing are some of the accelerating innovation areas, where adoption has been steadily increasing.
Innovation S-curve for artificial intelligence in the technology industry
Image smoothing is a key innovation area in artificial intelligence
Image smoothing, a method employed in image processing, aims to diminish noise and flaws present in digital images. The process entails the application of a filter or algorithm to the image data, which serves to blur or soften the boundaries and transitions between pixels, ultimately producing a cleaner and visually more appealing image.
GlobalData’s analysis also uncovers the companies at the forefront of each innovation area and assesses the potential reach and impact of their patenting activity across different applications and geographies. According to GlobalData, there are 780 companies, spanning technology vendors, established technology companies, and up-and-coming start-ups engaged in the development and application of image smoothing.
Key players in image smoothing – a disruptive innovation in the technology industry
‘Application diversity’ measures the number of applications identified for each patent. It broadly splits companies into either ‘niche’ or ‘diversified’ innovators.
‘Geographic reach’ refers to the number of countries each patent is registered in. It reflects the breadth of geographic application intended, ranging from ‘global’ to ‘local’.
Patent volumes related to image smoothing
|Company||Total patents (2010 - 2022)||Premium intelligence on the world's largest companies|
|ZTE||65||Unlock Company Profile|
|Fujifilm||220||Unlock Company Profile|
|Qualcomm||205||Unlock Company Profile|
|China Electronics Technology Group||140||Unlock Company Profile|
|Microsoft||107||Unlock Company Profile|
|Shanghai United Imaging Healthcare||131||Unlock Company Profile|
|Siemens||84||Unlock Company Profile|
|Apple||123||Unlock Company Profile|
|State Grid Corporation of China||69||Unlock Company Profile|
|Hitachi||49||Unlock Company Profile|
|Ricoh||96||Unlock Company Profile|
|Meta Platforms||109||Unlock Company Profile|
|Olympus||252||Unlock Company Profile|
|General Electric||98||Unlock Company Profile|
|ADOBE||119||Unlock Company Profile|
|Koninklijke Philips||209||Unlock Company Profile|
|Mitsubishi Electric||58||Unlock Company Profile|
|Nokia||84||Unlock Company Profile|
|Panasonic||74||Unlock Company Profile|
|Canon||571||Unlock Company Profile|
|Raytheon Technologies||56||Unlock Company Profile|
|Sony Group||508||Unlock Company Profile|
|IBM||51||Unlock Company Profile|
|Toshiba||68||Unlock Company Profile|
|NEC||105||Unlock Company Profile|
|Intel||101||Unlock Company Profile|
|SZ DJI Technology||146||Unlock Company Profile|
|Guangdong Oppo Mobile Telecommunications||426||Unlock Company Profile|
|Beijing ByteDance Technology||51||Unlock Company Profile|
|Beijing SenseTime Technology Development||77||Unlock Company Profile|
|Xiaomi||152||Unlock Company Profile|
|Shenzhen Sensetime Technology||65||Unlock Company Profile|
|Zhejiang Dahua Technology||98||Unlock Company Profile|
Source: GlobalData Patent Analytics
Among the companies innovating in image smoothing, Canon is one of the leading patents filers. The company’s patents are aimed at facilitating image processing tasks such as enhancing sharpness and achieving a smooth effect, while preserving image integrity. The solution entails an image processing device equipped with acquisition capabilities to gather multiple viewpoint images. Additionally, it incorporates contrast distribution generation features to derive a contrast distribution from these gathered viewpoint images. Other prominent patent filers in the space include Sony Group and Guangdong Oppo Mobile Telecommunications.
In terms of application diversity, Panasonic leads the pack, while Fujifilm and IBM stood in the second and third positions, respectively. By means of geographical reach, Meta Platforms held the top position, followed by Philips and Mitsubishi Electric.
Image smoothing plays a crucial role in AI by enhancing the quality of visual data, reducing noise, and improving the accuracy of image-based tasks such as object recognition or medical imaging analysis. This technique enables the extraction of more reliable features, leading to higher precision in AI-driven applications across various domains, from computer vision systems to medical diagnostics.
To further understand the key themes and technologies disrupting the technology industry, access GlobalData’s latest thematic research report on Artificial Intelligence (AI).