Image Processor Spatial Frequency Filtering Low-Resolution Displays
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Solution Overview
Problem
Current X-ray viewing stations require expensive high-resolution monitors to display digital image data comparable to X-ray films, limiting accessibility and increasing costs.
Innovation Solution
An image processor that suppresses spatial frequency components below a pre-defined or dynamic lower limit frequency band, allowing low-resolution screens to display high-pixel X-ray images by zooming into and panning through global images, enhancing local detail visibility while using low-cost monitors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expensive high-resolution monitors are used to display digital image data comparable with X-ray films, then image quality is improved, but device cost increases
Solution Approach 1:
The patent changes the parameter of spatial frequency representation by suppressing low-frequency components and enhancing high-frequency components through image processing algorithms. This transforms the image data to emphasize local details and edges, allowing standard monitors to display diagnostic-quality images without requiring expensive high-resolution displays.
Solution Approach 2:
The patent creates a processed copy of the original image data that emphasizes local details through frequency filtering. This processed copy is then displayed on standard monitors, effectively copying the diagnostic information needed for analysis while avoiding the need for expensive high-resolution display hardware.
2Ease of manufacture
If low-resolution screens are used to reduce cost, then device cost decreases, but local image detail visibility deteriorates
Solution Approach 1:
The patent modifies the frequency parameters of the image data by applying spatial frequency filtering. Low-frequency components are suppressed while high-frequency components are enhanced, changing the spectral characteristics of the image to emphasize local details that remain visible even on low-resolution screens.
Solution Approach 2:
The patent extracts and removes low-frequency components from the image data, which correspond to large-scale structures and gradients. By taking out these components, the remaining high-frequency information represents local details that can be effectively displayed on low-resolution screens without the distracting influence of large-scale variations.
3Measurement precision
If spatial frequency components below lower limit are suppressed, then local detail visibility is improved, but processing complexity increases
Solution Approach 1:
The patent segments the spatial frequency spectrum into different bands and applies selective processing to each segment. By dividing the frequency spectrum and processing each band separately through filtering operations, the system achieves enhanced local detail visibility while managing computational complexity through structured approach.
Solution Approach 2:
The patent implements frequency-selective processing by changing the parameter of spatial frequency representation. Through filtering operations that suppress low-frequency components and enhance high-frequency components, the system improves local detail visibility with controlled processing complexity.
Data Source
AI summary
An image processor and method for processing a sub-image (100a) specified within a global image (100). The processor (DZC) and the method yield a modified sub-image (100m) with spatial frequencies of large scale structures suppressed or removed and the modified sub-image is adapted to the dynamic grey value range of a screen (110) on which said modified sub-image (100m) is to be displayed.