Video Encoder Gradient Parameters for Computational Complexity
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently processing increasing amounts of digital video data, leading to high computational costs and complexity in encoding and decoding processes.
Innovation Solution
The proposed solution involves an encoder and decoder that use bi-directional optical flow to generate prediction images. This is achieved by deriving parameters based on pixel values and gradient values in reference images, allowing for the reduction of computational complexity by simplifying the multiplication operations required for pixel positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If bi-directional optical flow is used to generate prediction images, then coding efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent divides the computational process into distinct segments: gradient calculation for reference blocks, parameter derivation from gradients, and prediction image generation. By segmenting the bi-directional optical flow process, the patent reduces computational complexity while maintaining coding efficiency improvements.
Solution Approach 2:
The patent transforms the complex bi-directional optical flow computation into a simplified parameter-based approach. Instead of performing full optical flow calculations, the patent derives parameters (gradient values and their sums) from reference blocks and uses these parameters to generate prediction images, significantly reducing computational requirements.
2Measurement precision
If gradient values are calculated for multiple reference blocks, then prediction accuracy is improved, but processing amount increases
Solution Approach 1:
The patent extracts only the essential gradient information from reference blocks rather than processing complete pixel data. By calculating gradients and deriving parameters from these extracted features, the patent achieves improved prediction accuracy while minimizing the processing amount required.
Solution Approach 2:
The patent performs partial computation by calculating gradients only for necessary reference blocks and positions. Instead of exhaustive processing of all possible reference data, the patent selectively computes gradient values where they contribute most to prediction accuracy, reducing overall processing requirements.
Data Source
AI summary
An encoder includes circuitry and memory connected to the circuitry. The circuitry: derives an absolute value of a sum of gradient values in first and second ranges; derives, as a first parameter, a total sum of absolute values of sums of gradient values derived respectively for pairs of relative pixel positions; derives a pixel difference value between pixel values in the first and second ranges; inverts or maintains a plus or minus sign of the pixel difference value, according to a plus or minus sign of the sum of the gradient values indicating the sum of the gradient values in the first and second ranges; derives, as a second parameter, a total sum of pixel difference values each having the plus or minus sign inverted or maintained, the pixel difference values derived respectively for the relative pixel positions; and generates a prediction image using the first and second parameters.