Ahead of Image Sensors Asia 2025 we spoke to Young Woong Kim about his forthcoming presentation: Smart RGB-IR Sensor: Achieving Natural Color and Intelligent IR Noise Control.
Young Woong Kim | CTO at PIXELPLUS
I am currently serving as the Chief Technology Officer (CTO) at PIXELPLUS. With over 20 years of experience in analog circuit design including power amplifiers, display driver ICs, and image sensor ROICs, I have led initiatives in both product development and system level integration across complex analog and mixed signal systems.
For the past seven years, my focus has been on the development of CMOS image sensors, particularly for automotive surround view monitoring (SVM), in-cabin, and home appliance applications. I have been responsible for managing the entire development process from technology development to mass production, emphasizing performance, reliability, and cost-efficiency.
My areas of technical expertise include advanced sensor architectures and technologies such as RGB, RGB-IR, High Dynamic Range (HDR), LED Flicker Mitigation (LFM), Rolling Shutter, and Global Shutter.
I hold a Master’s degree in Electrical Engineering from POSTECH (Pohang University of Science and Technology).
Q: As the inaugural Asian edition of this renowned conference, what aspects of Image Sensors Asia 2025 are you most excited to participate in?
As an image sensor developer, I’d like to learn more about various technology trends of image sensor. And on behalf of my company, I also want people in this field to know that there’s an image sensor company in Korea called Pixelplus.
Q: Could you share some key themes from your upcoming presentation?
In this talk, I want to share two main technologies that make RGB-IR sensors more powerful.
The first is called Inverse Color Response Transformation (ICRT). It’s a smart color correction method that brings back natural RGB tones by carefully fixing the interference from IR signals.
The second is called Color Noise Adaptation(CNA). This one automatically adjusts color gain and noise levels depending on the balance between RGB and IR. Thanks to that, the sensor can improve RGB colors and cut down noise, while still keeping the useful IR information.
With these two, our new RGB-IR technology works well for both human viewing and machine recognition. It’s already being used in real products — like in-cabin monitoring systems, security cameras, face recognition, and even smart home appliances like robot vacuum cleaners.
Q: From your perspective, which emerging technology trends and application breakthroughs this year and next will most impact the image sensors sector?
It looks like 3D imaging technology — the kind that adds depth information beyond regular 2D images — is reaching a mature stage. You can see this in systems that connect stereo vision with AI processors, or in lidar products that use iTOF or dTOF sensors. The main uses will probably spread across areas like self-driving cars, robot vision, and smart farming.
Q: As a fast-growing market, what do you see in the Asian market in the next 5–10 years?
Humanoid robots — the ones that look like humans — are being imagined for homes. They could help people with daily life, like housework, education, or even taking care of the elderly.
