Camera Sensor Image Capture Degradation Detection
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Solution Overview
Problem
Image capture degradation in cameras due to factors like dirt accumulation, bird droppings, or environmental obstructions reduces image quality and can render images unusable, necessitating a method to determine and respond to such degradation.
Innovation Solution
A system and method that captures a series of image frames, generates a latent image by analyzing temporal and spatial differences, and performs a high-frequency multiscale fusion transform to identify image capture degradation, allowing for the selection of frequency-based coefficients and normalization to determine the extent of degradation, which triggers responses such as cleaning the camera or disregarding degraded regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image frames are captured continuously over time to detect degradation, then detection accuracy is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the image processing task by extracting specific features (gradient magnitude, gradient direction, intensity values) from image frames rather than processing entire images. This segmentation of processing focus reduces computational complexity while maintaining degradation detection accuracy through targeted analysis of relevant image characteristics.
Solution Approach 2:
The patent transitions from spatial domain analysis to frequency domain analysis by applying Fourier transform to the extracted image features. This dimensional change allows degradation patterns to be identified more efficiently in the frequency domain, reducing processing complexity while improving detection accuracy through spectral analysis.
2Measurement precision
If frequency-based decomposition is performed at multiple scales to improve degradation identification, then measurement precision is improved, but computational load increases
Solution Approach 1:
The patent applies partial action by performing frequency-based decomposition at selectively chosen scales rather than exhaustively analyzing all possible scales. This approach identifies degradation patterns at the most relevant scales while avoiding unnecessary computational energy consumption from analyzing less relevant frequency ranges.
Solution Approach 2:
The patent applies local quality by focusing computational resources on specific frequency bands and scales where degradation patterns are most prominent. Rather than uniformly processing all frequency scales, the system adapts its analysis depth to the local characteristics of the image data, reducing overall computational load while maintaining precision where it matters most.
Data Source
AI summary
A system for determining image capture degradation of a camera sensor is disclosed. The system is configured to capture a series of image frames by a camera of a vehicle over time. The system is configured to generate a latent image from a series of images captured by the camera. The system generates a plurality of frequency layers based on the latent image by, for example, performing a high frequency multiscale fusion transform. The system generates a plurality of frequency layers, each corresponding a spectral sub-band frequency, and each frequency layer includes the coefficients. The system generates a degradation map based on the processed activation map and generates an output based on the activation map. The output may be provided to an output system to wash the camera lens, notify a user or the vehicle of blockage, or modify image processing.