PATENT CLAIM ANALYSIS

Application Number: 15758967
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-02
Patent Classification: ["375", "240120"]

Abstract:
An intra prediction method includes the steps of: acquiring intra prediction mode information from a bitstream; deriving neighboring samples of a current block; determining an intra prediction mode for the current block on the basis of the intra prediction mode information; deriving a prediction sample of the current block on the basis of the intra prediction mode and the neighboring samples; determining filtering reference samples for the prediction sample on the basis of the intra prediction mode; and deriving a filtered prediction sample by applying filtering to the prediction sample on the basis of the filtering reference samples. According to the present invention, a prediction sample can be adaptively filtered according to the intra prediction mode, and intra prediction performance can be improved.

Claim (Index 3):
The intra-prediction method according to  claim 2 , wherein the category corresponding to the intra-prediction mode is determined on the basis of the following table, and a filter pattern used for the filtering depends on the category. Category Intra-prediction mode A 6, 7, 8, 9, 10, 11, 12, 13, 14 B 22, 23, 24, 25, 26, 27, 28, 29, 30 C 15, 16, 17, 18, 19, 20, 21 D 2, 3, 4, 5, 31, 32, 33, 34

Metadata:
- Claim Count in Document: 30.0
- Percentile: 90.0
- Lexical Diversity: 2.95556
- Patent Class: 375.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['13992468', '14730939', '15797895', '15344118', '15526076']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5687418995929026
- 35 USC 102 Novelty (BERT): 0.5199938194961236
- Combined Prediction Score: 0.5638670915832247
- Mean Citation Score: 301.676762
- Max Citation Score: 307.53064
- Similarity Product: 194.36599064705848

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test