VR Image Stitching Accelerator Using Region-Specific Processing
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Solution Overview
Problem
Existing VR image stitching processes suffer from distortion and inefficiencies due to the lack of specialized processing for stitching and image regions, leading to suboptimal VR image quality and generation speed.
Innovation Solution
An accelerator and storage device that divide original images into stitching and image regions, applying specialized processing to each region to improve stitching speed and reduce distortion, with iterative re-processing for high-distortion VR images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If uniform processing is applied to all regions of original images, then processing simplicity is maintained, but stitching speed and distortion reduction are insufficient
Solution Approach 1:
The patent divides the original image into two distinct regions: stitching regions (where images overlap and need alignment) and non-stitching regions (pure image content). This segmentation allows different processing strategies to be applied to each region, improving stitching speed by optimizing the stitching region processing while preserving image quality in non-stitching regions.
Solution Approach 2:
The patent applies different processing qualities to different regions: aggressive optimization and distortion correction are applied to stitching regions, while minimal processing is applied to non-stitching regions. This local quality approach ensures that processing complexity is concentrated where it is most needed (at boundaries) rather than uniformly applied across the entire image.
2Manufacturing precision
If aggressive distortion correction is applied to all image regions, then distortion is reduced, but image quality and processing efficiency deteriorate
Solution Approach 1:
By segmenting the image into stitching and non-stitching regions, the patent applies distortion correction only where necessary (at boundaries between images), avoiding unnecessary processing in pure image regions. This maintains high distortion correction precision at critical areas while preserving overall processing efficiency.
Solution Approach 2:
The patent applies high-quality distortion correction locally to stitching regions where it is most needed for seamless image blending, while applying minimal or no distortion correction to non-stitching regions. This local quality differentiation maintains manufacturing precision where it matters most while improving overall productivity.
3Productivity
If specialized processing is applied to stitching regions, then stitching speed and distortion reduction improve, but processing complexity increases
Solution Approach 1:
The processing architecture is segmented into distinct modules: a stitching region detector that identifies boundary regions, a stitching processor that handles stitching region processing, and an image processor that handles non-stitching region processing. This segmentation manages complexity by organizing specialized processing into dedicated components rather than a monolithic system.
Solution Approach 2:
The stitching region detector performs preliminary action by identifying stitching regions before the main processing occurs. This preliminary detection allows the system to prepare appropriate processing strategies in advance, reducing the complexity of real-time decision-making during the stitching and image processing phases.
Data Source
AI summary
An accelerator includes a memory access module configured to acquire a plurality of original images for generating a VR image from a input device, and a computing module including a stitching region detector, a stitching processor, an image processor, and a combination processor. The memory access module is configured to transmit the plurality of original images to the stitching region detector. The stitching region detector is configured to detect at least one stitching region and an image region from each of the plurality of original images by performing detection processing on each of the plurality of original images received from the memory access module, to provide the at least one stitching region to the stitching processor, and to provide the image region to the image processor. The stitching processor is configured to generate at least one post-processed stitching region.