Display Calibration via Photometric Observer Model
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Solution Overview
Problem
Current display calibration methods for medical imaging are subjective and prone to variability, often requiring external equipment and expertise, which can lead to inconsistent results and liability concerns due to the difficulty in ensuring proper DICOM GSDF compliance, especially in low-level grey shade regions.
Innovation Solution
A system and method for testing and calibrating displays that uses a test generator to display unpredictable test patterns with varying luminance or color differences, allowing users to identify patterns without external measuring equipment, and a processing arrangement to determine absolute luminance levels based on human visibility thresholds, enabling objective calibration and conformance checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If visual calibration methods are used without external measurement devices, then device complexity is reduced and ease of operation is improved, but measurement precision deteriorates due to subjectivity and human variability
Solution Approach 1:
The patent introduces an intermediary computational model (photometric observer) that translates subjective human visual responses into objective luminance measurements. The model acts as a mediator between the user's visual perception and the quantitative calibration data, allowing visual methods to achieve measurement precision comparable to physical instruments.
Solution Approach 2:
The patent replaces the mechanical/optical measurement system (external luminance meters and sensors) with a computational model based on human visual perception. Instead of using physical devices to measure luminance, the system uses a mathematical model of human vision to infer luminance levels from visual observations, thereby eliminating the need for complex external measurement equipment.
2Measurement precision
If quantitative calibration methods using external measurement devices are used, then measurement precision is improved, but device complexity increases and ease of operation deteriorates
Solution Approach 1:
The patent enables the display system to perform its own calibration using built-in test pattern generation and the photometric observer model, eliminating the need for external calibration equipment. The system serves itself by using its own display capabilities and a computational model to determine luminance levels, thereby reducing device complexity while maintaining measurement precision.
Solution Approach 2:
The patent creates a computational copy of human visual perception (the photometric observer model) that can process and interpret visual information in the same way the human eye and brain do. This computational copy allows the system to extract quantitative luminance data from visual observations without requiring physical measurement devices, thereby simplifying the calibration system.
3Ease of operation
If subjective visual calibration methods are used, then ease of operation is improved, but reliability deteriorates due to variability and liability concerns
Solution Approach 1:
The patent implements a feedback mechanism where the photometric observer model continuously refines luminance measurements based on visual observations of test patterns. The model provides objective feedback that eliminates subjectivity and variability, ensuring consistent and reliable calibration results while maintaining ease of operation through visual-based procedures.
4Measurement precision
If external measurement devices are used for calibration, then measurement precision is improved, but ease of operation deteriorates due to requirement for expertise and equipment
Solution Approach 1:
The patent creates a universal calibration method that can be applied to any display system without requiring specialized external equipment or expert knowledge. The photometric observer model serves multiple functions: it measures luminance, evaluates calibration accuracy, and provides guidance for adjustment, thereby simplifying the calibration process while maintaining measurement precision across different display types.
Data Source
AI summary
Testing a display involves display of a series of test patterns, each at a different luminance or color, and with a predetermined minimum difference of luminance or color from their background, each pattern being unpredictable to a user, and determining if the user has correctly identified the patterns. This can enable a more objective test without needing external measuring equipment. Calibrating the display involves determining an output luminance level by detecting a minimal difference of drive signal to give a just noticeable output luminance difference at a given high luminance drive level, and determining an absolute luminance of the given high input luminance level from the minimal difference and from a predetermined human characteristic of visibility threshold of luminance changes. This can avoid the need for an external or internal sensor. This can be useful during conformance checks or during calibration of the display for example.