Multi-Channel EVS Image Fusion for Runway Light Blooming
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Solution Overview
Problem
Traditional multi-channel enhanced vision systems experience image artifacts such as extreme light blooming when operating at high SWIR gain for early detection of runway lights, obscuring the runway environment, especially in adverse atmospheric conditions.
Innovation Solution
The system processes and fuses image data from both short-wave and long-wave radiation channels using nonlinear intensity transformation to produce low dynamic range image data, which are then combined to create a fused image with high brightness and detailed features, minimizing artifacts like blooming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If SWIR gain is increased to achieve early detection of runway lights, then detection capability is improved, but image artifacts such as extreme light blooming occur that obscure the runway environment
Solution Approach 1:
The patent segments the image processing into multiple channels (SWIR channel and LWIR channel) that operate independently but are combined to produce the final image. The SWIR channel processes short-wavelength infrared radiation while the LWIR channel processes long-wavelength infrared radiation, allowing each channel to be optimized for its specific wavelength range and reducing artifacts in the final composite image
Solution Approach 2:
The patent applies different gain parameters to different wavelength channels. By adjusting the gain of the SWIR channel separately from the LWIR channel, the system can optimize detection sensitivity for early runway light detection while controlling the blooming artifacts through the complementary LWIR channel data
2Loss of time
If SWIR gain is set very high to allow early detection of SW radiation sources, then detection timing is improved, but image quality deteriorates due to extreme blooming that obscures the runway environment
Solution Approach 1:
The patent merges the SWIR channel image data with the LWIR channel image data to create a composite enhanced vision image. This combination allows the system to utilize the early detection capability of the high-gain SWIR channel while the LWIR channel provides complementary information that reduces blooming artifacts and maintains overall image quality
Solution Approach 2:
The LWIR channel acts as an intermediary that mediates between the high-gain SWIR detection and the final image quality. The LWIR channel processes long-wavelength infrared radiation that is less susceptible to blooming, and its data is combined with the SWIR data to produce a final image that maintains both early detection capability and acceptable image quality
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 enables early detection of scene features and displays fine image detail, effectively addressing the issue of light blooming and enhancing situational awareness across various conditions.
Implementation Method 1
detect infrared radiation or visible light emanating from a scene. In the case of infrared radiation, typical EVS include one or more detectors that detect short-wavelength infrared radiation (SWIR) and long-wavelength infrared radiation (LWIR)
Data Source
AI summary
Processing of image data derived from radiation emanating from a scene and acquired by a multi-channel enhanced vision system renders an image of the scene for display. Detected first and second wavelength bands of radiation produce respective first and second sets of image data that include representations of relatively low contrast, high spatial frequency detail of features of the scene. Nonlinear intensity transformation of data derived from the first and second sets of image data produces, respectively, first and second sets of low dynamic range image data representing, respectively, first and second sets of intensity values. Different pairs of associated intensity values of the first and second sets correspond to different pixels forming an image. The associated intensity values of the different pairs are combined to form fused image data representing brightness levels of the pixels forming a displayed image that exhibits with high brightness and in great detail the features of the scene.