Scanned Object Imaging via Energy Absorption Color Mapping
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Solution Overview
Problem
Conventional image processing systems struggle to effectively distinguish elements in scanned objects due to limitations in human eye contrast perception, particularly in grayscale images, necessitating an improved system for enhanced image display and material detection.
Innovation Solution
A method and system that transform base images by comparing energy absorption information of pixels with reference values to highlight specific materials, using a processor-based material detection module, and display enhanced images with contrasting colors, while also incorporating dynamic range variation and layer removal techniques to improve visibility of obstructed objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional grayscale image display is used, then the system structure remains simple, but the human eye cannot distinguish elements effectively due to limited contrast perception
Solution Approach 1:
The patent applies color mapping to transform grayscale pixel values into color-coded representations. Different materials are assigned distinct colors based on their energy absorption characteristics, enabling the human eye to distinguish elements more effectively. This resolves the contradiction by enhancing element distinction through color visualization while maintaining relatively simple processing logic.
Solution Approach 2:
The patent transitions from a single-dimensional grayscale representation to a multi-dimensional color space representation. By mapping energy absorption values across multiple color channels (e.g., RGB), the system enables better human perception of material differences without significantly increasing system complexity.
2Measurement precision
If energy absorption comparison with reference values is performed for all pixels, then material detection accuracy improves, but processing time increases
Solution Approach 1:
The patent implements selective processing where only pixels with energy absorption values within a specific range or showing significant deviations from background are processed in detail. This partial action approach maintains high detection accuracy for relevant materials while reducing unnecessary processing of irrelevant pixels, thus balancing accuracy and processing time.
3Measurement precision
If multiple energy absorption components are analyzed, then material identification precision improves, but the complexity of processing increases
Solution Approach 1:
The patent segments the energy absorption analysis into distinct components (e.g., low-energy and high-energy components). Each component is processed separately and then integrated to form the final material identification. This segmentation allows complex multi-component analysis to be broken down into manageable steps, improving precision while controlling processing complexity through modular organization.
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
The system enhances visual differentiation of elements in scanned objects by highlighting relevant materials and improving visibility of obstructed objects, thereby overcoming the limitations of human eye contrast perception and existing image processing technologies.
Implementation Method 1
The base image is generated by capturing a source emission, for example an X-Ray emission, having traversed the object
Implementation Method 2
each pixel comprising energy absorption information
Data Source
AI summary
A technique for enhancing an image includes manipulating a base image to highlight pixels showing a particular material based on the energy absorption information of each pixel. In another technique, pixels in a base image are each converted to an output value to produce a converted image. Another technique allows imaging an obstructed object within a base image which is made of pixels, each representing a captured signal from a source emitting a source signal I0. An obstruction region contains pixels representing a combined signal I3 having traversed the obstructed object and an obstructive layer. Knowing a layer signal I2 representing a signal having traversed the obstructive layer outside of the obstruction region, the layer signal I2 may be removed from the combined signal I3, in order to reveal the original signal I1 representing an image of the obstructed object.