Vehicle Vision System Video Compression Using Indirect Context Model
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Solution Overview
Problem
Existing vehicle vision systems face challenges in efficiently processing and displaying exterior images from cameras while maintaining high image quality and low bandwidth requirements, particularly in real-time object detection and collision avoidance applications.
Innovation Solution
A vehicle vision system utilizing CMOS cameras and a lossy video compression codec based on vector quantization with an indirect context model, which allows for efficient compression and decompression of image data without requiring discrete wavelet or cosine transforms, enabling robust image processing and display with reduced bandwidth demands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional video compression codecs (MPEG2, H.264) are used, then compression efficiency is improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent extracts and removes the computationally intensive discrete wavelet transform (DWT) and discrete cosine transform (DCT) operations from the compression pipeline. By eliminating these complex mathematical transforms while retaining a simplified prediction-residual coding approach, the system achieves acceptable compression ratios without the heavy computational burden of conventional codecs.
Solution Approach 2:
The patent segments the video data processing into independent macroblock units with simple intra-prediction and motion compensation. By dividing the image into 16x16 pixel blocks and processing them independently with simplified algorithms, the system reduces overall computational complexity while maintaining compression effectiveness through block-based residual coding.
2Quantity of substance
If high compression rates are applied to reduce bandwidth, then transmission efficiency is improved, but image reconstruction quality deteriorates with increased artifacts
Solution Approach 1:
The patent applies preliminary prediction operations before compression to estimate and remove redundant information. By performing intra-prediction and motion compensation beforehand to generate predicted blocks, the system reduces the amount of actual data that needs to be transmitted, thereby achieving better compression ratios without sacrificing reconstruction quality.
Solution Approach 2:
The patent uses prediction to create copies of reference blocks that approximate the current block content. These predicted copies serve as proxies for the actual data, allowing the system to transmit only the differences (residuals) rather than full block data, thus maintaining reconstruction quality while reducing bandwidth requirements.
3Speed
If real-time processing is implemented for collision avoidance, then response time is improved, but processing power requirements increase
Solution Approach 1:
The patent removes computationally intensive transforms (DWT, DCT) from the real-time processing pipeline, retaining only simple prediction, subtraction, and entropy coding operations. This extraction of heavy computational elements enables real-time processing at lower power consumption while maintaining acceptable video quality for collision avoidance applications.
Solution Approach 2:
The patent applies partial processing by focusing computational resources on key areas such as motion detection and object regions, rather than uniformly processing entire frames. By prioritizing processing of relevant regions and using simplified algorithms, the system achieves real-time performance with reduced power requirements.
Data Source
AI summary
A multi-camera vision system of a vehicle includes at least four cameras disposed at a vehicle and having respective fields of view exterior of the vehicle. Each of the cameras is operable to capture image data representative of the respective field of view. Captured image data is compressed at the respective camera and the compressed image data is communicated to a control unit. The control unit includes an image processor operable to process image data. The image processor processes image data frame by frame using an indirect context model and without time wise dependency.