Shared Image Processing Operations Across ISP and Video Encoder
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Solution Overview
Problem
Existing image and video processing systems face inefficiencies due to redundant computations performed by different hardware components, such as image signal processors and video encoders, which increase computational burden and reduce performance.
Innovation Solution
Implementing a processing engine that identifies and performs common operations between different computing components, such as motion estimation and object detection, to generate shared data that can be used by multiple components, thereby reducing redundant computations and optimizing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If different computing components (image signal processor and video coder) perform separate operations on image data, then each component can be optimized for its specific function, but computational redundancy increases and processing efficiency decreases
Solution Approach 1:
The patent merges common operations between the image signal processor and video coder into a shared processing unit. Specifically, operations such as color space conversion, noise reduction, and other image processing functions are combined and executed once, with results shared by both components. This eliminates redundant computations while maintaining the functional independence and optimization of each component.
Solution Approach 2:
The patent creates a universal processing unit that serves multiple functions for both the image signal processor and video coder. This multi-functional unit handles operations required by both components, such as preliminary image processing tasks, allowing a single processing element to fulfill multiple roles and reduce overall computational burden on the system.
2Reliability
If redundant operations are performed by multiple hardware components, then each component can process data independently, but hardware resource burden increases significantly
Solution Approach 1:
The patent segments the processing architecture into distinct functional units: a shared processing unit for common operations and separate dedicated units for component-specific operations. This segmentation allows independent processing capability where each component can access its specialized processing unit while sharing common operations, reducing overall hardware resource burden through intelligent division of labor.
3Ease of operation
If common operations are performed separately by each computing component, then component independence is maintained, but processing time increases due to repetitive computations
Solution Approach 1:
The patent implements preliminary action by having the shared processing unit perform common operations once before the data is distributed to both the image signal processor and video coder. Operations such as color space conversion and noise reduction are executed in advance in the shared unit, so that both downstream components receive pre-processed data without needing to repeat these operations, thereby reducing processing time while maintaining component independence.
Data Source
AI summary
Systems, methods, and computer-readable media are provided for efficient control and data utilization between processing components of a system. An method can include obtaining image data captured by an image sensor; prior to a first computing component performing a first set of operations on the image data and a second computing component performing a second set of operations on the image data, determining one or more common operations included in the first set of operations and the second set of operations, wherein the first set of operations is different than the second set of operations; performing the one or more common operations on the image data; and generating an output of the one or more operations for use by the first computing component to perform the first set of operations and the second computing component to perform the second set of operations.