Non-uniformity Noise Measurement in Infrared Imaging
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Solution Overview
Problem
Current methods for measuring non-uniformity noise in infrared images or videos, such as signal-to-noise ratio and roughness indices, are not accurate and precise.
Innovation Solution
A method utilizing a model of scene statistics to measure non-uniformity noise in infrared images or videos by exploiting characteristics like shape and variance, generating a number signifying the magnitude of non-uniformity for each frame.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods like signal-to-noise ratio and roughness indices are used to measure non-uniformity noise, then the measurement process is simple, but the measurement precision is insufficient
Solution Approach 1:
The patent transforms the measurement approach by changing parameters from simple global metrics (signal-to-noise ratio, roughness index) to a multi-parameter statistical model that analyzes spatial frequency distributions, noise power spectral density, and natural scene statistics across multiple scales and orientations. This parameter transformation enables precise differentiation between non-uniformity noise and other noise types while maintaining practical measurability through standardized computational procedures
Solution Approach 2:
The patent replaces traditional mechanical/optical measurement systems with a computational analysis system that uses digital signal processing and statistical modeling. Instead of physical measurement devices, the system employs algorithms to analyze image data, compute noise power spectral densities, and apply natural scene statistics models, thereby achieving higher precision without additional hardware complexity
2Difficulty of detecting and measuring
If traditional noise measurement methods are used, then the ease of operation is high, but the ability to distinguish between different types of noise is poor
Solution Approach 1:
The patent segments the noise analysis into distinct spatial frequency components and statistical characteristics. By decomposing the noise power spectral density into different frequency bands and analyzing their individual properties, the method can differentiate between non-uniformity noise (which exhibits specific spatial frequency patterns) and other noise types (such as thermal noise or readout noise) that have different spectral signatures
Solution Approach 2:
The patent introduces natural scene statistics models as intermediary reference frameworks. These models provide expected statistical patterns for natural images under various conditions, serving as a mediator to compare against actual measured image statistics. This intermediary approach enables automatic differentiation between non-uniformity noise and other noise types by identifying deviations from expected natural scene patterns
Data Source
AI summary
A method, system and computer program product for measuring non-uniformity noise produced in images or videos (e.g., infrared images or videos). Images or videos, such as infrared images or videos, are captured. A model of scene statistics (statistical model of pictures, images or videos representative of pictures, images or videos, respectively, that are captured of the physical world) is utilized to measure the non-uniformity noise in the captured images or videos by exploiting exhibited characteristics for non-uniformity noise in the captured images or videos. A number signifying a magnitude of non-uniformity for each image or video frame is then generated. In this manner, non-uniformity noise produced in images or videos is measured.