Image Decoding Context Selection for Lower Memory HEVC Blocks
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Solution Overview
Problem
Existing image coding and decoding methods, particularly in High-Efficiency Video Coding (HEVC), suffer from increased memory usage due to the reliance on context models that utilize neighboring block values for control parameters, leading to inefficient memory management.
Innovation Solution
An image decoding and coding method that determines contexts for control parameters based on signal types, using neighboring blocks only under specific conditions, and employing a hierarchical depth to reduce memory usage, particularly for control parameters like split_coding_unit_flag, skip_flag, and others, while adapting to HEVC's hierarchical tree structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If context models utilizing neighboring block values are used for control parameters, then coding accuracy is improved, but memory usage increases
Solution Approach 1:
The patent applies local quality by differentiating context determination based on signal type. For first-type signal elements (intra-prediction modes, transform coefficients), neighboring block contexts are utilized to improve coding accuracy. For second-type signal elements (motion vectors, reference picture indices), current block contexts are used independently to reduce memory usage. This localized differentiation resolves the contradiction by applying context modeling only where it provides benefit.
Solution Approach 2:
The patent segments the control parameters into different categories (first-type and second-type signal elements) and applies different context determination methods to each segment. This segmentation allows the system to optimize for coding accuracy in some segments while reducing memory usage in others, thereby resolving the technical contradiction between precision and memory consumption.
2Productivity
If decoded control parameters of neighboring blocks are used for context determination, then coding efficiency is improved, but processing complexity increases
Solution Approach 1:
The patent reduces processing complexity by applying context determination selectively based on signal type. For second-type signal elements, only current block contexts are used, eliminating the need to access and process neighboring block data. This local化处理 reduces memory access operations and computational overhead while maintaining coding efficiency for the most critical parameters.
Data Source
AI summary
The image decoding method includes determining a context for use in a current block to be processed, from among a plurality of contexts, wherein in the determining: the context is determined under a condition that control parameters of a left block and an upper block are used, when the signal type is a first type; and the context is determined under a third condition that the control parameter of the upper block is not used and a hierarchical depth of a data unit to which the control parameter of the current block belongs is used, when the signal type is a third type, and the third type is one or more of (i) “merge_flag”, (ii) “ref_idx_l0” or “ref_idx_l1”, (iii) “inter_pred_flag”, (iv) “mvd_l0” or “mvd_l1”, (v) “intra_chroma_pred_mode”, (vi) “cbf_luma”, and (vii) “cbf_cb” or “cbf_cr”.