Display Range Calculation Using Noise Statistics
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Solution Overview
Problem
Conventional methods for setting display settings of display devices often result in either hiding weaker signals and noise or exaggerating noise, leading to low-quality image rendering, especially when dealing with data sets having strong signals or weak signals relative to noise.
Innovation Solution
A technique that calculates a display range based on the mean and standard deviation of the noise component of the signal, using a configurable multiplier, to optimize image display on display devices, which may involve filtering the data stream with a bilateral filter to reduce noise while preserving edges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If the conventional approach of scaling MIN and MAX intensity values to fit the display device dynamic range is used, then the display range is set, but weaker signals and noise become invisible or barely visible when the signal is very strong relative to noise
Solution Approach 1:
The patent changes the parameter basis from MIN/MAX intensity values to statistical parameters (mean μ and standard deviation σ) of the noise component. The display range is calculated as μ ± kσ, where k is a configurable multiplier. This statistical approach dynamically adapts the display range based on the actual noise characteristics of the data set, ensuring that weaker signals remain visible even when strong signals are present.
2Illumination intensity
If the conventional approach of scaling MIN and MAX intensity values is used, then the display range is set, but the fine grain of noise is exaggerated resulting in low quality image when there is no signal or weak signals relative to noise
Solution Approach 1:
The patent replaces the conventional MIN/MAX scaling parameters with statistical parameters (mean and standard deviation) that characterize the noise distribution. By using the standard deviation as the basis for display range calculation, the system inherently accounts for noise magnitude and prevents noise exaggeration, thereby maintaining image quality across different signal-to-noise conditions.
Solution Approach 2:
The system calculates the mean and standard deviation from the actual data stream, creating a feedback mechanism that adapts the display range to the specific characteristics of each data set. This feedback loop ensures that the display range is optimally adjusted based on the measured noise properties, preventing both signal loss and noise exaggeration.
3Manufacturing precision
If filtering the data stream with a bilateral filter is applied, then noise is reduced while preserving edges, but additional processing steps are required
Solution Approach 1:
The patent replaces complex mechanical filtering operations with a statistical calculation approach. Instead of applying bilateral filters or other complex image processing algorithms, the system simply calculates the mean and standard deviation of the noise component and uses these statistical parameters to set the display range. This substitution significantly reduces processing complexity while maintaining image quality.
Data Source
AI summary
A method for applying a filter to data to improve data quality and/or reduce file size. In one example, a region of interest of an image is identified. A histogram is generated of pixel intensity values in the region of interest. The histogram is iteratively updated to focus (zoom) in on the highest peak in the histogram. A Gaussian curve is fitted to the updated histogram. A bilateral filter is applied to the images, where parameters of the bilateral filter are based on the parameters of the Gaussian curve.