Shadow Compensation for Underground Structure Detection
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Solution Overview
Problem
Current methods fail to effectively detect and compensate for shadows in static infrared remote sensing images, leading to increased false alarm rates and reduced detectivity in zonal underground structure detection, such as underground rivers or tunnels.
Innovation Solution
A method that utilizes Digital Elevation Model (DEM) data, solar azimuth and altitude angles, and image processing techniques like median and mean filtering, dilation, and gray value compensation to detect and mitigate the effects of shadows in static infrared images, improving the accuracy of underground structure detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If shadow detection and compensation is performed in static infrared remote sensing images, then detection accuracy of underground structures is improved, but device complexity and processing difficulty increase
Solution Approach 1:
The patent performs preliminary shadow detection and compensation processing on the infrared remote sensing image before conducting underground structure detection. By pre-identifying shadow regions using elevation data and solar position calculations, and compensating for their effects in advance, the subsequent detection process operates on corrected data, thereby improving detection accuracy without requiring complex real-time processing during the actual detection phase.
2Measurement precision
If shadow compensation is performed to recover original features, then detection accuracy is improved, but processing time and loss of time increase
Solution Approach 1:
The shadow compensation process is executed as a preliminary step before the main detection task. By calculating shadow regions based on pre-acquired elevation data and solar position information, and applying compensation only to identified shadow areas, the method recovers original features efficiently without requiring extensive processing time during the actual detection operation.
Solution Approach 2:
The patent applies shadow compensation selectively only to identified shadow regions rather than processing the entire image uniformly. By localizing the compensation operation to specific areas where shadows are detected, the processing time is significantly reduced while still achieving the goal of recovering original features in affected regions, thereby improving detection accuracy without excessive time cost.
3Difficulty of detecting and measuring
If DEM data and multiple processing steps are used for shadow detection, then shadow detection capability is improved, but ease of operation decreases
Solution Approach 1:
The patent performs preliminary acquisition and preparation of DEM elevation data and solar position information before the shadow detection process. By having these data ready in advance, the actual shadow detection operation can proceed systematically through automated processing steps, improving detection capability while the structured workflow maintains operational simplicity through clear sequential steps.
Solution Approach 2:
The shadow detection and compensation process is divided into distinct sequential steps: (1) acquiring elevation data, (2) calculating shadow regions based on solar position, (3) compensating shadow effects in identified areas, and (4) performing underground structure detection. This segmentation transforms a complex task into manageable, operationally simple steps that can be executed systematically, improving both detection capability and ease of operation.
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 effectively reduces the impact of shadows on underground structure detection, enhancing the accuracy of detection and reducing false alarm rates in static infrared images.
Implementation Method 1
Shadow is a common physical phenomenon in nature, and is generated when a light source is blocked by an object
Implementation Method 2
performing median filtering processing thereon
Implementation Method 3
performing mean filtering processing on the altitude image
Implementation Method 4
performing dilation processing on the obtained shadow position labeled image
Data Source
AI summary
A zonal underground structure detection method based on sun shadow compensation is provided, which belongs to the crossing field of remote sensing technology, physical geography and pattern recognition, and is used to carry out compensation processing after a shadow is detected, to improve the identification rate of zonal underground structure detection and reduce the false alarm rate. The present invention comprises steps of acquiring DEM terrain data of a designated area, acquiring an image shadow position by using DEM, a solar altitude angle and a solar azimuth angle, processing and compensating a shadow area, and detecting a zonal underground structure after the shadow area is corrected. In the present invention, the acquired DEM terrain data is used to detect the shadow in the designated area; and the detected shadow area is processed and compensated, to reduce influence of the shadow area on zonal underground structure detection; finally, the zonal underground structure is detected by using a remote sensing image after shadow compensation, so that the accuracy of zonal underground structure detection is improved and the false alarm rate is reduced compared with zonal underground structure detection using a remote sensing image without shadow compensation processing.