Samsung electronics co., ltd. (20240161244). METHOD AND APPARATUS WITH IMAGE PROCESSING simplified abstract
Contents
- 1 METHOD AND APPARATUS WITH IMAGE PROCESSING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD AND APPARATUS WITH IMAGE PROCESSING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
METHOD AND APPARATUS WITH IMAGE PROCESSING
Organization Name
Inventor(s)
Seunghoon Jee of Suwon-si (KR)
METHOD AND APPARATUS WITH IMAGE PROCESSING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240161244 titled 'METHOD AND APPARATUS WITH IMAGE PROCESSING
Simplified Explanation
The abstract describes a processor-implemented method for estimating a transformation model using a neural network model, motion sensor data, and image frames to generate output image data.
- Transformation model estimated using a neural network model
- Motion sensor data used to represent motion between image frames
- Global motion between image frames determined for transformation
- Output image data generated by combining image frames using the transformation model
Potential Applications
This technology could be applied in various fields such as:
- Video stabilization in cameras
- Augmented reality applications
- Virtual reality systems
Problems Solved
This technology helps in:
- Improving image quality by reducing motion blur
- Enhancing video stability
- Enabling smoother transitions between frames
Benefits
The benefits of this technology include:
- Enhanced image and video quality
- Improved user experience in AR and VR applications
- Increased accuracy in motion tracking
Potential Commercial Applications
This technology could be commercially used in:
- Smartphone cameras
- Security cameras
- Gaming consoles
Possible Prior Art
One possible prior art for this technology could be the use of optical flow algorithms in video processing to estimate motion between frames.
Unanswered Questions
How does this technology handle complex motion patterns in video frames?
This article does not delve into the specifics of how the neural network model adapts to complex motion patterns in video frames.
What is the computational overhead of implementing this technology in real-time applications?
The article does not address the computational resources required to implement this technology in real-time scenarios.
Original Abstract Submitted
a processor-implemented method includes estimating a transformation model using a transformation determination neural network model, provided motion sensor detected motion data representing motion of an image sensor with respect to a first image frame and a subsequent second image frame from captured by the image sensor, to perform a transformation based on global motion between the first image frame and the second image frame, and generating output image data by combining, by using the transformation model, the first image frame and the second image frame.
