AI Image Processing Device Bandwidth Latency Contradiction
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Solution Overview
Problem
Traditional image sensors face a resolution-bandwidth mismatch, where they can process high-resolution images but are limited by the narrow bandwidth of data communication links, leading to latency in transmitting high-resolution data.
Innovation Solution
An AI-based image data processing method that reduces the resolution of frame image data to a lower bandwidth-compatible resolution, identifies regions of interest (ROI) with AI recognition, and modifies their resolution based on priority, allowing for efficient transmission while maintaining key content specificity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution image data is transmitted through the data communication link, then image quality is maintained, but transmission latency increases due to limited bandwidth
Solution Approach 1:
The image data is segmented into multiple resolution levels. Full-resolution data is processed locally for immediate decisions, while lower-resolution summaries are transmitted for remote analysis. This segmentation allows simultaneous optimization of both local response time and remote analysis quality.
Solution Approach 2:
Different regions of the image are assigned different quality levels based on their importance. Critical regions (ROIs) maintain higher resolution while less important areas are transmitted at lower resolution, optimizing the trade-off between overall image quality and transmission bandwidth utilization.
2Loss of information
If full-resolution frame image data is transmitted, then complete information is preserved, but data transmission bandwidth requirements exceed available capacity
Solution Approach 1:
The system extracts and transmits only the essential information needed for remote processing. By identifying and extracting key features and regions of interest, the system preserves critical information while dramatically reducing the total data volume that needs to be transmitted across the bandwidth-constrained link.
Solution Approach 2:
The patent introduces a temporal dimension to image transmission by sending a sequence of lower-resolution frames that capture motion and change over time, rather than transmitting a single high-resolution static image. This allows remote systems to reconstruct important details from temporal patterns while using less bandwidth.
3Productivity
If resolution is reduced to match bandwidth capacity, then transmission efficiency improves, but image recognition accuracy deteriorates
Solution Approach 1:
The system performs preliminary processing at the edge device to identify regions of interest and extract key features before transmission. This preliminary action ensures that the most important information is preserved and highlighted in the transmitted data, maintaining recognition accuracy even at lower resolutions.
Solution Approach 2:
The patent dynamically adjusts transmission parameters such as resolution, compression ratio, and frame rate based on current bandwidth conditions, scene complexity, and detected motion. This adaptive parameter adjustment maintains optimal transmission efficiency while preserving sufficient image quality for accurate recognition under varying conditions.
Data Source
AI summary
An image data processing method includes receiving, from an image sensor, frame image data of a frame at a first resolution, reducing a resolution of the frame image data to a second resolution, performing image recognition on the frame image data to determine one or more regions of interest (ROI) and a priority level of each of the one or more ROIs, and extracting portions of the frame image data corresponding to the one or more ROIs. The method further includes modifying a resolution of the portions of the frame image data corresponding to the one or more ROIs based on the priority level of the ROIs, and combining the resolution-modified portions of the frame image data corresponding to the one or more ROIs with the frame image data at the second resolution to generate output frame image data.