HDR Video Editing with Mask-Guided Alpha Map Allocation
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Solution Overview
Problem
Existing video editing technologies face challenges in managing memory usage efficiently during high dynamic range (HDR) video editing, leading to performance deterioration due to the high memory requirements for storing alpha information and editing data, especially when blending images with different color spaces.
Innovation Solution
The solution involves reusing memory areas for alpha information storage and employing mask information for pixel-based editing functions, such as doodle and sticker blending, by allocating alpha maps only when necessary, thereby reducing memory usage and maintaining video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If alpha information is stored for each pixel during HDR video editing, then blending accuracy is improved, but memory usage increases
Solution Approach 1:
The patent segments the blending process into two distinct stages: a decision stage that determines whether blending is needed (using minimal mask information), and an execution stage that performs actual blending (using full alpha information). This segmentation allows the system to maintain high blending accuracy when needed while avoiding unnecessary memory allocation when blending is not required, directly resolving the contradiction between blending precision and memory consumption.
Solution Approach 2:
The patent implements partial action by storing only mask information (partial data) during the decision stage instead of complete alpha information. This partial storage approach consumes minimal memory while still enabling accurate blending decisions. The full alpha information is allocated temporarily only when blending is actually executed, ensuring that memory is used efficiently without compromising blending accuracy when required.
2Productivity
If additional memory is allocated for video editing, then editing performance is improved, but device complexity increases
Solution Approach 1:
The patent implements dynamic memory allocation where the system adaptively adjusts memory usage based on the actual editing requirements. During the decision stage, minimal memory is used for mask operations. When blending is determined to be necessary, the system dynamically allocates alpha maps only for those specific frames or regions. This dynamic approach maintains high editing performance while avoiding the complexity of permanently allocating large memory buffers, as memory is allocated on-demand rather than statically.
Solution Approach 2:
The system performs self-service by automatically determining when blending is needed through mask information analysis, and autonomously allocating or deallocating alpha maps without requiring external intervention or complex memory management protocols. This self-managing approach simplifies the overall system architecture while maintaining high editing performance, as the system serves its own memory management needs efficiently.
3Quantity of substance
If mask information is used for pixel-based editing, then memory efficiency is improved, but blending flexibility is reduced
Solution Approach 1:
The patent applies preliminary action by pre-storing mask information that encodes blending decisions before actual blending operations. These masks are generated during video decoding or preprocessing stages, preparing the data structure for efficient later use. This preliminary preparation maintains memory efficiency during storage while enabling flexible blending operations when needed, as the pre-computed masks can be quickly referenced and expanded into full alpha maps only when required, thus preserving both memory efficiency and blending flexibility.
Solution Approach 2:
The patent uses mask information as an intermediary between the compact decision-making stage and the full-featured blending execution stage. The mask serves as a lightweight mediator that contains essential blending guidance without requiring full alpha map data. This intermediary structure maintains memory efficiency during the decision phase while enabling complete blending flexibility during execution, as the mask can be expanded or interpreted into various blending modes without losing the underlying flexibility options.
Data Source
AI summary
Disclosed is an electronic device comprising memory storing instructions, and at least one processor comprising processing circuitry. The instructions, when executed by the at least one processor individually and/or collectively, cause the electronic device to: acquire a first image; generate a first input frame to be blended with the first image, wherein each piece of pixel data of the first input frame includes RGB data and mask information indicating a blending method of each piece of pixel data; allocate, to the first input frame, a first alpha map including alpha values for each pixel for the first input frame; determine a blending method for frame color blending of the first input frame and the first image, based on the mask information; perform frame color blending on the first input frame and a second input frame of the first image, based on the determined blending method and the first alpha map; and output a second image generated by the frame color blending.


