Multi-scale filter pyramid for image fusion noise reduction
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Solution Overview
Problem
Existing imaging technologies, such as those described in Waxman et al. U.S. Pat. No. 5,555,324, lose image information at scales other than the processor's scale and enhance high-frequency noise due to reliance on single-scale center-surround processors with limited spatial interactions.
Innovation Solution
The use of multi-scale processing and multi-neighborhood center-surround operators to combine images from multiple sensors, employing a multi-scale filter pyramid where center-surround operators of increasing scale enhance images at respective scales, preserving complementary information across multiple detail levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single-scale center-surround processors are used to enhance image information, then the processor can enhance information at its specific scale, but it loses image information at other scales and enhances high-frequency noise
Solution Approach 1:
The patent divides the image processing into multiple scales by creating a pyramid structure with multiple levels of center-surround processors. Each level processes different scale information, allowing the system to preserve and enhance information across all scales simultaneously rather than losing information at scales other than the current processor's scale.
Solution Approach 2:
The patent adds a scale dimension to the traditional single-scale processing approach by implementing a multi-scale pyramid structure. This dimensional extension allows the system to process and preserve information at multiple scales concurrently, resolving the contradiction between enhancing information at one scale and losing information at other scales.
2Device complexity
If single-scale center-surround processors are used, then the processing is simple, but the system enhances high-frequency noise
Solution Approach 1:
The patent segments the processing task across multiple scales in a pyramid structure. By distributing the processing workload across different levels, each handling specific scale information, the system reduces the enhancement of high-frequency noise at any single scale while maintaining overall processing effectiveness.
Solution Approach 2:
The patent changes the scale parameter across multiple levels of processing. By varying the scale at which center-surround operators apply their enhancement, the system selectively enhances information at appropriate scales while suppressing high-frequency noise that would be amplified by single-scale processing.
3Adaptability or versatility
If multiple sensors with different capabilities are used to image the same scene, then complementary operational capabilities are achieved, but the fusion process becomes complex
Solution Approach 1:
The patent creates a universal multi-scale pyramid structure that can process images from multiple sensors with different capabilities. The same multi-scale center-surround operator framework handles fusion of diverse sensor data, making the system adaptable to various sensor types while managing complexity through a unified processing architecture.
Solution Approach 2:
The patent segments the fusion process into multiple scales, allowing different sensor capabilities to be integrated at appropriate levels. This segmentation enables the system to handle the complexity of multi-sensor fusion by processing information hierarchically rather than attempting to fuse all sensor data simultaneously at a single level.
Data Source
AI summary
A multi-scale filter pyramid is applied to one or more components of a multi-component input image to produce a fused and enhanced image that can be mapped to a display, such as a color display.