Pulse Latency Coding for Luminance-Invariant Visual Signal Encoding
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Solution Overview
Problem
Existing computer vision systems struggle to encode visual signals in a way that is insensitive to luminance and contrast, making it difficult to process and transmit visual information effectively, particularly in varying light conditions.
Innovation Solution
The system encodes visual signals into pulse-code output by using the relative timings of pulses, where the pattern of relative latencies is invariant to changes in luminance and contrast, achieved through the use of a generator signal and scaling parameters calculated from the image signal's history, allowing for adaptive encoding and decoding of visual features across multiple channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional pulse encoding is used, then the system can transmit visual information, but the encoding is sensitive to luminance and contrast changes
Solution Approach 1:
The patent transforms the encoding parameter from absolute pulse timing to relative pulse latency. By measuring the time difference between pulses rather than their absolute timing, the system becomes invariant to luminance and contrast changes while maintaining reliable information transmission about visual features.
2Adaptability or versatility
If adaptive scaling is applied to maintain optimal latency intervals, then the system adapts to varying light conditions, but the calculation complexity increases
Solution Approach 1:
The system employs feedback mechanisms where the scaling parameter is continuously adjusted based on the history of generator signals. The low-pass filter processes past signal values to produce a scaling parameter that adapts the pulse latency to current lighting conditions, creating a closed-loop adaptive system.
Solution Approach 2:
The patent calculates the scaling parameter in advance using a low-pass filter on historical generator signal data before it is needed for pulse latency determination. This preliminary calculation prepares the adaptive parameter ahead of time, reducing real-time computational complexity during critical pulse generation moments.
3Productivity
If pulse latency is used to encode visual features, then information transmission efficiency improves, but slow adaptation to low or high luminance levels occurs
Solution Approach 1:
The system dynamically adjusts the pulse latency based on real-time lighting conditions through the scaling parameter. By making the latency adaptive rather than fixed, the system maintains optimal information transmission efficiency across varying luminance levels while adapting to new conditions as they arise.
Data Source
AI summary
Systems and methods for processing image signals are described. One method comprises obtaining a generator signal based on an image signal and determining relative latencies associated with two or more pulses in a pulsed signal using a function of the generator signal that can comprise a logarithmic function. The function of the generator signal can be the absolute value of its argument. Information can be encoded in the pattern of relative latencies. Latencies can be determined using a scaling parameter that is calculated from a history of the image signal. The pulsed signal is typically received from a plurality of channels and the scaling parameter corresponds to at least one of the channels. The scaling parameter may be adaptively calculated such that the latency of the next pulse falls within one or more of a desired interval and an optimal interval.