PATENT CLAIM ANALYSIS

Application Number: 16010926
Application Type: Utility
Filing Date: 2018-06
Publication Date: 2018-12
Patent Classification: ["375", "240120"]

Abstract:
A method for intra-prediction estimation is provided that includes determining a best intra-prediction mode for a block of samples, wherein at least some of the neighboring samples used for intra-prediction estimation include approximate reconstructed samples, applying approximate reconstruction to the block of samples using the best intra-prediction mode to generate a block of approximate reconstructed samples, and storing the block of approximate reconstructed samples for use in intra-prediction estimation of other blocks of samples.

Claim (Index 1):
A method for intra-prediction estimation, the method comprising:\n determining, by at least one processor, a best intra-prediction mode for a first block of samples; applying, by the at least one processor, approximate reconstruction to the first block of samples using the best intra-prediction mode, to generate a block of approximate reconstructed samples; storing, by the at least one processor, the block of approximate reconstructed samples; generating, by the at least on processor, an intra-predicted block of samples for a second block of samples based on the best intra-prediction mode and the block of approximate reconstructed samples, comprising generating at least one sample of the intra-predicted block of samples by linearly interpolating at least two samples of the block of approximate reconstructed samples; generating, by the at least one processor, a block of residual samples based on the intra-predicted block of samples and the second block of samples; generating, by the at least one processor, a block of transform coefficients based on the block of residual samples; quantizing, by the at least one processor, the block of transform coefficients, to generate a quantized block of transform coefficients; and entropy encoding, by the at least one processor, the quantized block of transform coefficients.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 94.0
- Lexical Diversity: 2.0
- Patent Class: 375.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['14038536', '15108764', '15709270', '13658807', '13914387']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5274035765182631
- 35 USC 102 Novelty (BERT): 0.516583772064134
- Combined Prediction Score: 0.5263215960728502
- Mean Citation Score: 316.692358
- Max Citation Score: 321.80908
- Similarity Product: 239.38472136848685

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