Cubic Spline Luminance Mapping for Adaptive Dynamic Range
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Solution Overview
Problem
Conventional image dynamic range adjustment methods result in loss of luminance levels and reduced luminance contrast due to inflexible mapping curves, leading to poor display effects on both high and low dynamic range display devices.
Innovation Solution
The method employs cubic spline curves to map luminance values of pixels based on histogram information, adjusting the dynamic range by determining interpolation points and modifying the mapping curve segments to enhance flexibility and protect specific luminance intervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a conventional mapping curve is used to adjust dynamic range, then the processing is simple, but luminance levels are lost and luminance contrast is reduced
Solution Approach 1:
The mapping curve is divided into multiple segments, each corresponding to a different luminance interval. Each segment can be independently adjusted using cubic spline curves, allowing precise control over luminance levels in different ranges while maintaining overall processing simplicity.
Solution Approach 2:
The mapping curve transitions from a static conventional curve to a dynamic adjustable curve using cubic splines. The curve can be flexibly adjusted based on histogram information of different luminance intervals, enabling adaptive luminance mapping that preserves both simplicity and precision.
2Device complexity
If a fixed mapping curve is used for dynamic range adjustment, then the device complexity is low, but adaptability to different display devices is poor
Solution Approach 1:
The mapping curve parameters are made variable rather than fixed. By using cubic spline curves with adjustable control points and weights, the mapping curve can be adapted to different display devices with varying dynamic ranges, maintaining low base complexity while enabling high adaptability.
Solution Approach 2:
The cubic spline-based mapping curve serves multiple functions: it can adapt to different display device types (SDR and HDR), handle different luminance intervals, and preserve luminance contrast. This multi-functionality achieves universal adaptability without significantly increasing device complexity.
3Loss of time
If conventional luminance mapping is applied, then the processing time is short, but luminance contrast is not obvious and display effect is poor
Solution Approach 1:
Different luminance intervals are processed with different mapping characteristics. By applying cubic spline curves specifically to intervals where luminance contrast needs enhancement, the method achieves high luminance contrast without requiring excessive processing time across the entire image range.
Solution Approach 2:
The conventional mechanical-like step-by-step luminance mapping is replaced with a more efficient cubic spline interpolation approach. This substitution maintains processing speed while significantly improving luminance contrast through smoother, more precise luminance value transformation.
Data Source
AI summary
This application provides an image dynamic range processing method and apparatus. The method includes: obtaining a first coordinate value of a first interpolation point and a first coordinate value of a third interpolation point related to a first cubic spline curve; and determining, based on histogram information of a first luminance interval of a to-be-processed image, a first coordinate value of a second interpolation point related to the first cubic spline curve. The first luminance interval is an interval between the first coordinate value of the first interpolation point and the first coordinate value of the third interpolation point. The first coordinate value of the first interpolation point, the first coordinate value of the second interpolation point, and the first coordinate value of the third interpolation point are used to determine a function of the first cubic spline curve.