VR Image Processing Region-Based Compression
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Solution Overview
Problem
Existing VR devices have limitations in hardware MIPI transmission bandwidth and CPU/GPU processing speed, resulting in low frame rates, which cause user dizziness and affect the VR experience.
Innovation Solution
An image processing method that compresses the data of moving objects in VR images based on a target compression ratio, reducing the number of pixels and data amount without affecting visual quality, thereby improving frame rates and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If image data is transmitted at full resolution, then visual quality is maintained, but transmission bandwidth and processing speed requirements increase, resulting in low frame rates
Solution Approach 1:
The image is divided into multiple regions based on depth information, with different compression strategies applied to each region. Foreground regions containing moving objects use lower compression ratios to maintain visual quality, while background regions use higher compression ratios to reduce data amount, thereby increasing overall frame rate without significantly compromising visual experience
Solution Approach 2:
Different compression quality levels are applied to different spatial regions of the image. The region of interest (foreground) maintains higher quality with lower compression, while less important regions (background) accept higher compression. This local differentiation allows the system to prioritize visual quality where it matters most while reducing overall data transmission requirements
2Productivity
If compression ratio is increased to reduce data amount, then frame rate improves, but visual quality deteriorates
Solution Approach 1:
The compression ratio is dynamically adjusted based on the importance of different image regions. Foreground regions use lower compression ratios to preserve visual quality, while background regions use higher compression ratios. This dynamic, region-adaptive approach allows the system to achieve higher effective frame rates without noticeable quality degradation in important areas
3Reliability
If full resolution image data is processed, then image quality is preserved, but processing bandwidth requirements increase beyond hardware capabilities
Solution Approach 1:
The image processing system segments the image into multiple depth-based regions and applies different processing strategies to each segment. This segmentation allows the system to process only necessary portions of the image at full resolution (foreground) while using compressed representations for other portions (background), reducing overall processing bandwidth requirements to match hardware capabilities
Solution Approach 2:
The system maintains high processing quality locally in the region of interest while accepting lower quality in background regions. This local quality preservation approach ensures that critical visual information is processed at full resolution while non-critical areas use reduced processing, making the system compatible with existing hardware bandwidth constraints
Data Source
AI summary
An image processing method and apparatus, an electronic device and a storage medium are disclosed. The method comprises: acquiring a current frame of image; detecting a moving object in the current frame of image to obtain a region of interest and a background region, wherein the region of interest includes the moving object; compressing image data of the region of interest to obtain first image data after compressed; and outputting the first image data after compressed and background picture data corresponding to the background region to a display device to display the current frame of image by the display device.