PATENT CLAIM ANALYSIS

Application Number: 15972372
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-09
Patent Classification: ["375", "240250"]

Abstract:
A higher coding efficiency for coding a significance map indicating positions of significant transform coefficients within a transform coefficient block is achieved by the scan order by which the sequentially extracted syntax elements indicating, for associated positions within the transform coefficient block, as to whether at the respective position a significant or insignificant transform coefficient is situated, are sequentially associated to the positions of the transform coefficient block, among the positions of the transform coefficient block depends on the positions of the significant transform coefficients indicated by previously associated syntax elements. Alternatively, the first-type elements may be context-adaptively entropy decoded using contexts which are individually selected for each of the syntax elements dependent on a number of significant transform coefficients in a neighborhood of the respective syntax element, indicated as being significant by any of the preceding syntax elements.

Claim (Index 14):
The apparatus according to  claim 8 , wherein the position sub-scan order is adaptively selected from a plurality of scan orders including a diagonal scan order.

Metadata:
- Claim Count in Document: 72.0
- Percentile: 93.0
- Lexical Diversity: 2.22727
- Patent Class: 375.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: True
- Related Applications: ['14944012', '15200300', '15940820', '15195504', '13648538']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.6437441868483449
- 35 USC 102 Novelty (BERT): 0.5943944198683436
- Combined Prediction Score: 0.6388092101503448
- Mean Citation Score: 523.651598
- Max Citation Score: 548.3697
- Similarity Product: 402.9056010052622

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