PATENT CLAIM ANALYSIS

Application Number: 16038154
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2020-01
Patent Classification: ["375", "240020"]

Abstract:
A method based on CTU level rate-distortion optimization for rate control in video coding which can effectively improve the perceptual rate-distortion performance and coding efficiency is provided. Firstly, a perceptual rate-distortion model is established using a divisive normalization framework, which characterizes the relationship between local visual quality and coding bits. Subsequently, the established perceptual rate-distortion model is applied to overall distortion optimization which is transformed into a global optimization problem and solved with convex optimization algorithms to obtain optimal CTU level coding bit allocation.

Claim (Index 6):
An encoding method according to  claim 1 , wherein the optimization of R-D performance further comprises:\n converting a perceptual rate distortion cost function J to: J = \u2211 i = 1 N \ue89e D \u2032 \ue8a0 ( R i ) + \u03bb ( R C - \u2211 i = 1 N \ue89e R i ) , where \u03bb is the Lagrangian multiplier, D\u2032(R i )is the perceptual distortion of the i-th CTU with a coding bit rate R I , and N is the number of CTUs in the frame, R c , is the target frame-level coding bit of the current frame of the input video; and\n determining one or more optimal CTU level coding bit by: \n R j * = k j \u2211 i = 1 N \ue89e k i \ue89e R c , where R j  is the initial CTU level coding bit for the jth CTU in the current frame.

Metadata:
- Claim Count in Document: 16.0
- Percentile: 95.0
- Lexical Diversity: 1.52542
- Patent Class: 375.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15352222', '16016691', '15260302', '12832495', '11530042']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4797746726076782
- 35 USC 102 Novelty (BERT): 0.5352061097250479
- Combined Prediction Score: 0.4853178163194153
- Mean Citation Score: 279.06874200000004
- Max Citation Score: 346.58685
- Similarity Product: 242.5222292246461

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

Dataset: test