18319872. METHOD AND APPARATUS WITH IMAGE PROCESSING simplified abstract (Samsung Electronics Co., Ltd.)
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 18319872 titled 'METHOD AND APPARATUS WITH IMAGE PROCESSING
Simplified Explanation
The processor-implemented method described in the abstract involves estimating a transformation model using a neural network model, motion sensor data, and image frames to generate output image data.
- Estimating a transformation model using a neural network model
- Utilizing motion sensor data to represent motion of an image sensor
- Generating output image data by combining image frames using the transformation model
Potential Applications
This technology could be applied in:
- Image stabilization in cameras
- Video editing software for seamless transitions
Problems Solved
This technology helps in:
- Correcting for global motion between image frames
- Improving image quality by reducing motion blur
Benefits
The benefits of this technology include:
- Enhanced image quality
- Improved user experience in capturing and editing images/videos
Potential Commercial Applications
The potential commercial applications of this technology could be in:
- Smartphone cameras
- Security cameras for surveillance systems
Possible Prior Art
One possible prior art for this technology could be:
- Image stabilization algorithms used in digital cameras
Unanswered Questions
How does this technology handle complex motion patterns in images?
This technology uses a neural network model to estimate transformation models, but it is not clear how it handles complex motion patterns in images. Further details on the neural network's capabilities in analyzing intricate motion patterns would provide more insight.
What is the computational overhead of implementing this technology in real-time applications?
While the abstract mentions a processor-implemented method, it does not specify the computational resources required for real-time applications. Understanding the computational overhead of this technology would be crucial for assessing its feasibility in practical 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.
