Halation Analysis for Surface Particle Detection
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Solution Overview
Problem
Conventional methods fail to accurately distinguish between atmospheric and surface-based visual limitations in camera images, such as halations, leading to inefficient countermeasures and potential unnecessary energy consumption or equipment wear.
Innovation Solution
A method that analyzes the intensity distribution of halations in camera images to differentiate between surface-shaped and volume-shaped particle distributions, using radial intensity profiles and Mie theory-based classification to determine the cause of visual limitations, enabling targeted countermeasures like particle removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used to detect visual limitations in camera images, then detection can be performed, but the ability to accurately distinguish between atmospheric and surface-based halations is insufficient
Solution Approach 1:
The patent segments the halation analysis process into distinct components: detecting the halation region, analyzing the intensity distribution pattern, and classifying the cause (atmospheric vs. surface-based). This segmentation allows for precise identification by breaking down the complex detection task into manageable analytical steps, each focusing on specific characteristics of the halation.
Solution Approach 2:
Instead of directly detecting particle distribution, the patent inverts the approach by analyzing the light intensity distribution pattern caused by particle scattering. By examining how light is scattered and distributed in the image rather than directly detecting particles, the system can infer particle distribution characteristics and distinguish between atmospheric and surface-based halations.
2Loss of energy
If targeted countermeasures are implemented without accurate halation classification, then energy can be saved, but ineffective countermeasures may be applied leading to equipment wear
Solution Approach 1:
The patent implements a feedback mechanism where the analyzed halation characteristics (intensity distribution patterns) provide information about the cause of the halation. This feedback enables the system to select appropriate countermeasures: for atmospheric halations, no particle removal is needed (saving energy), while for surface-based halations, targeted particle removal is activated (ensuring effectiveness). The classification result directly feeds into the countermeasure selection process.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for precise identification and efficient removal of surface-based halations, reducing energy consumption and equipment wear by distinguishing between atmospheric and surface-based visual limitations, thereby improving image quality.
Implementation Method 1
The halation can be caused for example by diffraction or scattering of light beams emanating from a light source
Implementation Method 2
The halation can be caused for example by diffraction or scattering of light beams emanating from a light source on atmospheric particles
Implementation Method 3
The origin of halations can be described for example using the theory published in 1908 by Gustav Mie, and later named for him, concerning light scattering on spherical particles
Data Source
AI summary
A method for processing an image representing at least one halation. The image is read in via an interface to an image recording device. In addition, using the image an intensity distribution representing the halation is ascertained. The intensity distribution is then analyzed in order to determine a surface-shaped distribution of particles in the region of acquisition of the image recording device as the cause of the halation, and to distinguish it from a volume-shaped distribution of particles.