Spike Signal Display Method for High-Speed Motion Resolution
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Solution Overview
Problem
Traditional image sensors fail to capture dynamic changes in scenarios due to fixed frame rates, leading to redundancy, low time domain resolution, and blurring during high-speed motion, and existing machine learning algorithms cannot directly process spike signals from new types of cameras that collect spike array signals.
Innovation Solution
A spike signal-based display method and system that analyze spike sequences to obtain spike-firing information, accumulate pixel values, adjust them based on specific amounts and thresholds, and filter them to generate high-quality images that can be used by machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image sensors perform complete sampling at fixed frame rate, then all spatial positions are captured uniformly, but time domain resolution is low and motion blurring occurs during high speed motion
Solution Approach 1:
The patent transforms the static fixed-frame-rate sampling into dynamic event-driven sampling. The sensor continuously monitors pixel positions and triggers sampling only when illumination intensity changes exceed a threshold, making the sampling rate adaptive to scene dynamics. This resolves the contradiction by capturing temporal details only when necessary, eliminating redundancy while maintaining time domain resolution for moving objects.
Solution Approach 2:
The patent changes the sampling parameter from fixed time intervals to variable event-triggered intervals. By monitoring illumination intensity changes and triggering samples based on threshold exceedance, the system dynamically adjusts sampling density according to scene activity. This parameter transformation eliminates redundant uniform sampling while preserving critical temporal information.
2Productivity
If traditional image sensors use fixed frame rate sampling, then sampling is simple to implement, but oversampling or undersampling occurs causing redundancy or motion blurring
Solution Approach 1:
The patent implements feedback by continuously monitoring illumination intensity at each pixel position and comparing it against threshold values. The sampling decision is based on feedback from previous samples and current scene conditions. This feedback mechanism ensures sampling occurs efficiently only when scene changes warrant capture, improving both productivity and reliability simultaneously.
Solution Approach 2:
The system dynamically adjusts sampling behavior based on real-time scene conditions. When illumination changes are detected, sampling is triggered; when stable, sampling is suppressed. This dynamic adaptation eliminates the oversampling/undersampling problem of fixed frame rates while maintaining capture accuracy.
3Measurement precision
If spike signals are collected with high time resolution, then dynamic changes are captured accurately, but existing machine learning algorithms cannot directly process these signals
Solution Approach 1:
The patent introduces an intermediary processing layer that transforms spike signals into a format compatible with existing machine learning algorithms. The system accumulates spike events, applies spatial and temporal filtering, and generates intermediate representations that bridge the gap between event-based sensor output and traditional algorithm input requirements, maintaining both time resolution and algorithm compatibility.
Solution Approach 2:
The patent transforms the data representation parameters from sparse event coordinates to dense pixel intensity values through accumulation and filtering operations. This parameter transformation converts the spike signal format into something familiar to existing machine learning pipelines while preserving the temporal precision information through the accumulation process.
Data Source
AI summary
A spike signal-based display method and a spike signal-based display system are disclosed by the present application. The method includes: analyzing a spike sequence corresponding to a single pixel position to obtain spike-firing information; acquiring respective pixel values corresponding to multiple spike-firing times before a single spike-firing time, and accumulating the pixel values as a first accumulated pixel value; setting a first specific amount corresponding to the single spike-firing time of the pixel position, and summing the first specific amount and the first accumulated pixel value to obtain a first pixel value of the pixel position; comparing the first pixel value with a pixel threshold range, and obtaining a second specific amount based on the first specific amount; and obtaining a second pixel value of the pixel position by summing the first accumulated pixel value and the second specific amount, and generating an image by using the second pixel values. Since the pixel values are calculated using the time domain characteristic of the spike signal, an image with high quality is formed and an image at any continuous time instant is output. The quality of the generated image is improved by adjusting the pixel values based on the pixel threshold range.