Local Illumination Compensation for Virtual Pipeline Data Units
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Solution Overview
Problem
Current video coding techniques face challenges in efficiently compressing video data while maintaining high quality, particularly due to the large amounts of data required for high fidelity and resolution, which burdens communication networks and devices, and existing illumination compensation methods are complex and inefficient.
Innovation Solution
The proposed method involves a system and method for improved local illumination compensation using a virtual pipeline data unit (VPDU) processing structure, where current neighbor samples, reference neighbor samples, and additional neighbor samples are used to determine illumination compensation parameters for video blocks spanning multiple VPDUs, enabling efficient compensation without complex subsampling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional illumination compensation methods are used, then video quality is maintained, but computational complexity increases and processing efficiency decreases
Solution Approach 1:
The patent divides the video processing into virtual pipeline data units (VPDUs) that can be processed independently and in parallel. By segmenting the illumination compensation task into smaller VPDU units, the computational complexity is reduced while maintaining video quality, as each VPDU can be processed separately without requiring complex global computations.
Solution Approach 2:
The patent performs preliminary actions by collecting neighbor samples and determining illumination compensation parameters before actual video block processing. This preliminary preparation of compensation parameters for multiple VPDUs reduces the computational burden during the main processing stage, thereby decreasing overall computational complexity while preserving video quality.
2Manufacturing precision
If high fidelity video data is used, then video quality improves, but data volume increases burdening networks and devices
Solution Approach 1:
The patent changes the parameter representation by using illumination compensation parameters (scaling factors and offsets) that describe lighting variations rather than transmitting full high-fidelity video data. This parameter-based approach maintains video quality by accurately representing illumination changes while significantly reducing the data volume that needs to be transmitted and processed.
Solution Approach 2:
The patent applies local illumination compensation to specific regions (VPDUs and their neighboring blocks) rather than processing entire video frames globally. This localized approach maintains high video quality in each region while reducing overall data volume, as only local compensation parameters need to be transmitted and processed rather than complete high-fidelity data for the entire video.
Data Source
AI summary
Techniques are described herein for processing video data. For instance, a current block of a picture of the video data can be obtained, and it can be determined that the current block includes more than one virtual pipeline data unit (VPDU). Current neighbor samples for the current block, reference neighbor samples for the current block, and additional neighbor samples for the current block can be obtained for illumination compensation. One or more illumination compensation parameters can be determined for the current block using the current neighbor samples, the reference neighbor samples, and the additional neighbor samples. The additional neighbor samples are used for determining the one or more illumination compensation parameters based on the current block covering more than one VPDU. Illumination compensation can be performed for the current block using the one or more illumination compensation parameters.