Histogram Correlation Stability via Gaussian Low Pass Filtering
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Solution Overview
Problem
Histogram correlation algorithms face instability due to small disturbances in input signals/images, particularly exacerbated by discrete and narrowly concentrated chromaticity histograms, leading to fluctuating correlation scores in image and video processing.
Innovation Solution
The method involves computing and smoothing histograms using low pass filtering, specifically applying a Gaussian low pass filter to both input and reference signals, and shifting the target histogram within a neighborhood to combine correlation scores, thereby stabilizing the correlation results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If histogram correlation is performed on discrete chromaticity histograms with peaks in close proximity, then correlation score computation is straightforward, but the correlation score becomes unstable and fluctuates with small disturbances in input signal
Solution Approach 1:
The patent applies low pass filtering to the chromaticity histograms before performing correlation computation. This preliminary smoothing action removes high-frequency variations and discrete peak effects, making the correlation score more stable against small input disturbances while maintaining computational feasibility
2Reliability
If low pass filtering is applied to smooth histograms, then correlation score stability improves, but computational complexity and processing time increase
Solution Approach 1:
The patent modifies the histogram representation by applying low pass filtering with specific filter parameters to smooth the chromaticity distribution. This parameter change transforms the discrete histogram into a continuous smooth distribution, improving correlation stability while the filter design balances smoothing effectiveness with computational efficiency
Data Source
AI summary
A method and apparatus for improving stability of histogram correlation based image and video processing algorithms. The method includes computing a histogram for target signal and reference signal for generating a target histogram and a reference histogram, performing low pass filtering of the input signal and the reference signal and producing smoothed histograms, and performing correlation on the smoothed histograms for improving stability of histogram correlation.