Samsung electronics co., ltd. (20240129546). ARTIFICIAL INTELLIGENCE-BASED IMAGE ENCODING AND DECODING APPARATUS, AND IMAGE ENCODING AND DECODING METHOD THEREBY simplified abstract
Contents
- 1 ARTIFICIAL INTELLIGENCE-BASED IMAGE ENCODING AND DECODING APPARATUS, AND IMAGE ENCODING AND DECODING METHOD THEREBY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ARTIFICIAL INTELLIGENCE-BASED IMAGE ENCODING AND DECODING APPARATUS, AND IMAGE ENCODING AND DECODING METHOD THEREBY - 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 Unanswered Questions
- 1.11 Original Abstract Submitted
ARTIFICIAL INTELLIGENCE-BASED IMAGE ENCODING AND DECODING APPARATUS, AND IMAGE ENCODING AND DECODING METHOD THEREBY
Organization Name
Inventor(s)
Quockhanh Dinh of Suwon-si (KR)
Kwangpyo Choi of Suwon-si (KR)
ARTIFICIAL INTELLIGENCE-BASED IMAGE ENCODING AND DECODING APPARATUS, AND IMAGE ENCODING AND DECODING METHOD THEREBY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240129546 titled 'ARTIFICIAL INTELLIGENCE-BASED IMAGE ENCODING AND DECODING APPARATUS, AND IMAGE ENCODING AND DECODING METHOD THEREBY
Simplified Explanation
The abstract describes an artificial intelligence-based image decoding method where a transform block is obtained from a bitstream, a transform kernel is generated using a neural network, a residual block is obtained by applying the transform kernel to the transform block, and the current block is reconstructed using the residual block and a prediction block.
- Transform block obtained from bitstream
- Transform kernel generated using neural network
- Residual block obtained by applying transform kernel
- Current block reconstructed using residual block and prediction block
Potential Applications
This technology could be applied in various fields such as image and video compression, computer vision, and image recognition systems.
Problems Solved
This technology helps in improving image decoding efficiency, reducing data storage requirements, and enhancing image quality.
Benefits
The benefits of this technology include faster image decoding, better compression ratios, and improved image reconstruction accuracy.
Potential Commercial Applications
Potential commercial applications of this technology include use in video streaming services, surveillance systems, medical imaging devices, and autonomous vehicles.
Possible Prior Art
One possible prior art could be traditional image decoding methods that do not utilize artificial intelligence for image reconstruction.
Unanswered Questions
How does the neural network learn to generate the transform kernel?
The abstract mentions that a neural network is used to generate the transform kernel, but it does not elaborate on the training process or the specific architecture of the neural network.
What is the computational complexity of the image decoding process using this method?
The abstract does not provide information on the computational resources required to implement this artificial intelligence-based image decoding method.
Original Abstract Submitted
an artificial intelligence (ai)-based image decoding method and an apparatus performing the ai-based image decoding method are provided. according to the ai-based image decoding method, a transform block for a residual block of a current block is obtained from a bitstream, a transform kernel for the transform block is generated by applying, to a neural network, a prediction block for the current block, neighboring pixels of the current block, and coding context information, the residual block is obtained by applying the generated transform kernel to the transform block, and the current block is reconstructed by using the residual block and the prediction block.
