Multi-Modal Camera Image Blending with Dynamic Quality Weighting
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Solution Overview
Problem
Different types of images captured by cameras under varying environmental conditions may have differing quality levels, leading to suboptimal composite images when blended with equal weighting, which limits visual enhancement.
Innovation Solution
A dynamic weighting approach is used to blend images based on a dynamic quality proxy, adjusting the contribution of each image type according to its quality, determined from metadata such as analog gain, temperature range, or other camera settings, to form a composite image with improved overall quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If images from different camera types are blended with equal weighting, then the composite image can be formed, but the overall quality is limited due to inclusion of lower quality images
Solution Approach 1:
The patent applies dynamics by making the weighting factors variable rather than fixed. The weighting for each camera type is dynamically adjusted based on environmental conditions detected by sensors (light level, temperature) and image quality metrics (signal-to-noise ratio, temperature range). This allows the system to adaptively emphasize higher quality images while de-emphasizing lower quality ones, resolving the contradiction between forming a composite and maintaining high quality.
Solution Approach 2:
The system changes parameters (weighting factors) based on measured conditions. When ambient light is low, the weighting for low-light cameras is increased while color cameras are de-emphasized. When temperature variations are small, thermal camera weighting is reduced. This parameter adjustment based on environmental and quality metrics allows the composite image to maintain high quality by excluding noisy contributions.
2Manufacturing precision
If dynamic weighting based on quality proxy is used, then higher quality composite images are achieved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-defining quality proxies for different camera types (analog gain for low-light cameras, temperature range for thermal cameras). These proxies are calculated in advance from readily available metadata and sensor readings before the blending process. This preliminary quality assessment simplifies the subsequent weighting calculation, reducing the complexity burden while maintaining adaptive quality optimization.
Solution Approach 2:
The patent introduces intermediary elements (quality proxies and weighting factors) that mediate between the raw camera images and the final composite. Rather than directly comparing and blending raw images, the system uses these intermediary quality metrics to determine appropriate weighting, which simplifies the blending process and makes the system more manageable despite the added complexity of dynamic adjustment.
Data Source
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AI summary
Examples are disclosed that relate to blending different types of images captured by different types of cameras employing different sensing modalities based on a dynamic weighting. The dynamic weighting is calculated based on a dynamic quality proxy that serves as an approximation of image quality that may change from image to image. In one example, a first image of a scene is received from a first camera. A dynamic quality proxy is received. A second image of the scene is received from a second camera with a different sensing modality than the first camera. A composite image blended from the first and second images in proportion to a dynamic weighting that is based on the dynamic quality proxy is output.