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 2):
An encoding method according to  claim 1 , further comprising:\n dividing each CTU into a number, I, of sub-blocks for Direct Cosine Transform (DCT); and obtaining the divisive normalization factor, f, from Structural Similarity (SSIM) index in DCT domain by: f = 1 l \ue89e \u2211 i = 1 l \ue89e \u2211 j = 1 N L - 1 \ue89e ( U i \ue8a0 ( j ) 2 + V i \ue8a0 ( j ) 2 ) N L - 1 + C 1 E ( \u2211 j = 1 N L - 1 \ue89e ( U \ue8a0 ( j ) 2 + V \ue8a0 ( j ) 2 ) N L - 1 + C 1 ) , where E( ) is the expectation operation in the frame, U(j) and V(j) are the DCT coefficients of the input and reconstructed signals, respectively, U i (j) and V i (j) are the corresponding j-th DCT coefficient in the i-th sub-block, respectively, C I  is the constant in accordance with the definition of SSIM index, and N L  is the sub-block size.

Metadata:
- Claim Count in Document: 16.0
- Percentile: 95.0
- Lexical Diversity: 1.52542
- Patent Class: 375.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15352222', '16016691', '15260302', '12832495', '11530042']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4502036819950938
- 35 USC 102 Novelty (BERT): 0.5328912742883147
- Combined Prediction Score: 0.4584724412244159
- Mean Citation Score: 279.06874200000004
- Max Citation Score: 346.58685
- Similarity Product: 243.0111671727419

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