Lg electronics inc. (20240187605). INTER-PREDICTION METHOD AND DEVICE BASED ON DMVR AND BDOF simplified abstract
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INTER-PREDICTION METHOD AND DEVICE BASED ON DMVR AND BDOF
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INTER-PREDICTION METHOD AND DEVICE BASED ON DMVR AND BDOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240187605 titled 'INTER-PREDICTION METHOD AND DEVICE BASED ON DMVR AND BDOF
- Simplified Explanation:**
The patent application describes an image decoding method that utilizes decoder-side motion vector refinement to improve the accuracy of motion vectors and prediction samples for a current block. This method involves deriving refined motion vectors, generating prediction samples based on these refined vectors, and creating recovery samples from the prediction samples.
- Key Features and Innovation:**
- Decoder-side motion vector refinement (DMVR) for improved motion vector accuracy.
- Prediction sample generation based on refined motion vectors.
- Recovery sample generation from prediction samples.
- Determination of bi-directional optical flow (BDOF) process based on picture order count (POC) differences.
- Potential Applications:**
This technology can be applied in video compression, streaming services, video editing software, and virtual reality applications.
- Problems Solved:**
This technology addresses issues related to motion vector accuracy, prediction sample generation, and recovery sample quality in image decoding processes.
- Benefits:**
- Improved image quality in video decoding.
- Enhanced motion vector accuracy.
- Better prediction sample generation for smoother video playback.
- Commercial Applications:**
Potential commercial applications include video streaming services, video editing software, virtual reality content creation tools, and video compression technologies.
- Prior Art:**
Prior art related to this technology may include methods for motion vector refinement in video coding standards such as H.264 and H.265.
- Frequently Updated Research:**
Research on improving motion vector accuracy and prediction sample generation in image decoding processes may provide valuable insights for further advancements in this technology.
- Questions about Image Decoding Method:**
1. How does decoder-side motion vector refinement contribute to improving image quality in video decoding? 2. What are the potential implications of using bi-directional optical flow processes in the image decoding method?
Original Abstract Submitted
an image decoding method according to the present document is characterized in that: decoder-side motion vector refinement (dmvr) is applied to derive refined l0 and l1 motion vectors on the basis of l0 and l1 motion vectors of the current block; prediction samples of the current block are derived on the basis of l0 prediction samples derived on the basis of the refined l0 motion vector and l1 prediction samples derived on the basis of the refined l1 motion vector; and recovery samples of the current block are generated on the basis of the prediction samples, wherein the l0 prediction samples are derived on the basis of an l0 reference picture and the refined l0 motion vector, the l1 prediction samples are derived on the basis of an l1 reference picture and the refined l1 motion vector, and in the step for deriving the prediction samples, whether to apply a bi-directional optical flow (bdof) process is determined on the basis of whether a first poc difference between the current picture and the l0 reference picture and a second poc difference between the current picture and the l1 reference picture are the same.
