Multiplanar Image API for Interoperability and Resource Efficiency
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Solution Overview
Problem
Current computing systems face inefficiencies in processing and interoperability of images and videos stored in different formats, leading to resource wastage and compatibility issues when converting formats to enable usage by various applications.
Innovation Solution
The implementation of an API that imports and manages images in a multiplanar format, allowing separate access and processing of planes within the image, such as intensity and color values, enabling interoperability between different computing contexts and formats like NV12.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If images are stored in different formats, then interoperability between computing contexts is improved, but computing resources are wasted converting formats
Solution Approach 1:
The patent segments image data into separate planar components (Y plane for luminance, UV planes for chrominance) stored in a multiplanar format. This segmentation allows different computing contexts to access and process only the specific planes needed, eliminating the need for complete format conversion and reducing computing resource wastage while maintaining interoperability.
Solution Approach 2:
The patent introduces a multiplanar format as an intermediary representation that bridges different image formats and computing contexts. By storing images in this intermediate multiplanar structure, the system enables interoperability between different formats without requiring resource-intensive conversion operations, thus reducing computing resource wastage.
2Adaptability or versatility
If images are converted to different formats, then compatibility with applications is improved, but processing time and resources increase
Solution Approach 1:
By segmenting images into separate planar components in the multiplanar format, the system enables applications to access and process only the specific planes required for their functionality. This eliminates the need for complete format conversion, significantly reducing processing time and resources while maintaining broad compatibility.
Solution Approach 2:
The multiplanar format performs preliminary organization of image data into separable planes during storage, so that when applications need to access specific information, the data is already divided and ready for direct access. This preliminary structuring eliminates the need for time-consuming format conversion operations.
3Productivity
If separate access to image planes is enabled, then processing efficiency is improved, but system complexity increases
Solution Approach 1:
The multiplanar format serves as a universal storage structure that can accommodate different image formats and application requirements through a single unified interface. This multi-functionality allows the system to provide separate plane access for various applications without requiring multiple specialized systems, thereby improving processing efficiency while managing complexity through universality.
Data Source
AI summary
Apparatuses, systems, and techniques to perform an API to retrieve a portion of an image based, at least in part, on an indication of the portion of said image. In at least one embodiment, an API uses a handle that references a memory location for said image, and said image has a first plane corresponding to image data (e.g., color) and a second plane corresponding to different image data (e.g., intensity). Apparatuses, systems, and techniques to perform an API to retrieve a portion of an image based, at least in part, on an indication of the portion of the image.