Dynamic Prediction Error Computation Adjustment for Video Processing

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Solution Overview

Problem

Conventional video processing systems face challenges in efficiently managing prediction error reduction computations, which require significant computational resources and power, especially in devices with limited capabilities, due to the high data rate of uncompressed video and the complexity of existing compression techniques.

Innovation Solution

A video processing system dynamically adjusts prediction error reduction computations based on the amount of motion in the image data and available memory resources, using a dynamic computation adjustment module to determine whether to perform sub-integer pixel interpolation, thereby optimizing resource utilization and reducing processing time and power consumption.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If conventional video compression techniques (DPCM, DCT, motion compensation) are used to compress video data, then video data transmission and storage becomes feasible, but significant computational resources and power are consumed

Engineering Contradiction:

Improvevideo data sizeVSAvoidcomputational power consumption

Core Design Contradiction:

Quantity of substanceVSUse of energy by moving object

Solution Approach 1:

The patent implements dynamic adjustment of prediction error computation resources based on scene complexity metrics. The system transitions from static computational allocation to dynamic allocation, adjusting the level of prediction error reduction computations according to real-time analysis of motion magnitude and buffer fullness, thereby resolving the contradiction between compression effectiveness and power consumption

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent changes key parameters including prediction error threshold, buffer fullness threshold, and motion magnitude threshold to optimize the balance between compression efficiency and computational cost. By dynamically adjusting these parameters based on scene characteristics, the system achieves effective video compression while adapting power consumption to actual processing needs

Inventive Principle:

Principle #35Parameter changes

2Manufacturing precision

If prediction error reduction computations are increased to improve compression efficiency, then video quality is maintained, but processing time and power consumption increase

Engineering Contradiction:

Improvevideo compression qualityVSAvoidprocessing time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent applies partial action by selectively performing prediction error reduction computations only when scene complexity metrics indicate it is necessary. Instead of uniformly applying full computation resources to all video frames, the system performs computations partially and selectively based on motion magnitude and buffer conditions, reducing overall processing time while maintaining quality where needed

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent implements feedback mechanisms that continuously monitor compression efficiency, buffer fullness, and scene complexity. This feedback drives dynamic adjustment of computation resources, allowing the system to optimize the balance between processing speed and video quality by learning from actual performance data and adapting computation levels accordingly

Inventive Principle:

Principle #23Feedback

3Productivity

If sub-integer pixel interpolation is performed to reduce prediction error, then compression efficiency improves, but computational complexity and resource usage increase significantly

Engineering Contradiction:

Improvecompression efficiencyVSAvoidcomputational complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent applies local quality by performing sub-integer pixel interpolation selectively in regions of the video frame where it provides the most benefit. Instead of uniformly applying complex interpolation to entire frames, the system focuses computational resources on specific blocks or regions based on motion analysis and prediction error metrics, thereby improving compression efficiency while limiting the increase in overall computational complexity

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent segments the video processing task into multiple stages including motion estimation, prediction error calculation, and selective interpolation. By dividing the processing into discrete segments that can be independently evaluated and optimized, the system reduces overall computational complexity while maintaining compression efficiency through targeted application of sub-integer interpolation where most beneficial

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS9479794B2Resource efficient video processing via prediction error computational adjustments

Publication Date: 2016.10.25 NXP USA INC

AI summary

A video processing system dynamically adjusts video processing prediction error reduction computations in accordance with the amount of motion represented in a set of image data and/or available memory resources to store compressed video data. In at least one embodiment, video processing system adjusts utilization of prediction error computational resources based on the size of a prediction error between a first set of image data, such as current set of image data being processed, and a reference set of image data relative to an amount of motion in a current set of image data. Additionally, in at least one embodiment, the video processing adjusts utilization of prediction error computation resources based upon a fullness level of a data buffer relative to the amount of motion in the current set of image data.