Video Encoding Power Optimization via Rate-Distortion Analysis
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Solution Overview
Problem
Conventional video encoders in portable devices face high power consumption due to motion estimation, which is not optimized for limited power resources, leading to suboptimal rate-distortion values and inefficient power-bit-rate-visual quality tradeoffs.
Innovation Solution
A method that computes a power-rate-distortion value by estimating the power consumption of video processing devices during the encoding process, allowing the selection of power-friendly prediction functions to balance power consumption, bit-rate, and visual quality by incorporating power consumption into the rate-distortion criterion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional motion estimation is used in portable video encoders, then encoding capability is provided, but power consumption becomes excessively high
Solution Approach 1:
The patent applies dynamics by making the prediction function selection adaptive and variable rather than fixed. The encoder dynamically selects from multiple prediction functions (spatial, temporal, gradient, Laplacian) based on local image characteristics and rate-distortion optimization, allowing the system to adapt its power consumption and encoding capability to the specific content being encoded.
Solution Approach 2:
The patent changes parameters by introducing a new rate-distortion criterion that incorporates power consumption as an additional parameter alongside traditional distortion metrics. This modified criterion enables the system to optimize for both encoding quality and power efficiency simultaneously, resolving the contradiction between these two objectives.
2Reliability
If conventional rate-distortion optimization is used, then encoding quality is optimized, but power consumption is not considered leading to suboptimal performance in portable devices
Solution Approach 1:
The patent modifies the rate-distortion optimization criterion by adding power consumption as a third parameter to the traditional rate-distortion tradeoff. This extended criterion allows the system to simultaneously optimize for encoding quality, bit rate, and power consumption, ensuring reliable encoding performance while respecting power constraints in portable devices.
Solution Approach 2:
The patent implements feedback by using the computed rate-distortion-power value to guide the selection of prediction functions. The system evaluates multiple prediction functions, computes their respective costs including power consumption, and selects the function that minimizes the overall criterion, creating a closed-loop optimization process.
3Measurement precision
If multiple prediction functions are evaluated to improve quality, then encoding accuracy increases, but computational complexity and power consumption increase
Solution Approach 1:
The patent applies segmentation by dividing the prediction function selection into distinct categories (spatial, temporal, gradient, Laplacian) and further segmenting the optimization process by evaluating functions separately for different block types and motion characteristics. This structured approach manages computational complexity while maintaining encoding accuracy.
Solution Approach 2:
The patent implements partial action by selectively applying different prediction functions to different blocks based on their characteristics, rather than uniformly applying the most accurate function to all blocks. This approach achieves sufficient encoding accuracy for each local region while reducing overall computational complexity and power consumption.
Data Source
AI summary
The present invention relates to a method of encoding a sequence of pictures, a picture being divided into blocks of data, said encoding method comprising the steps of:—computing a residual error block from a difference between a current block contained in a current picture and a candidate area using of a prediction function,—computing an entropy of the residual error block,—computing an overall error between said current block and said candidate area,—estimating a power consumption of a video processing device adapted to implement said prediction function,—computing a rate-distortion value on the basis of the entropy, the overall error and the estimated power consumption of the video processing device,—applying the preceding steps to a set of candidate areas using a set of prediction functions in order to select a prediction function according to the rate-distortion value.