Histogram-Guided Cubic Spline Curves for Image 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 dynamic range (HDR) and standard dynamic range (SDR) 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 form of the mapping curve to enhance flexibility and protect specific luminance intervals, thereby improving display quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a conventional mapping curve is used to adjust dynamic range, then the mapping process is simple, but luminance levels are lost and luminance contrast is reduced
Solution Approach 1:
The patent divides the mapping curve into multiple segments, each handled by a different cubic spline curve. This segmentation allows different luminance intervals to be processed with different mapping characteristics, preserving luminance levels while maintaining computational feasibility.
Solution Approach 2:
The patent employs dynamic cubic spline curves that can be adjusted based on histogram information of the image data. The curves are not fixed but can be dynamically generated to match the specific luminance distribution, enabling both simplicity and precision.
2Productivity
If a fixed mapping curve is used, then the processing is fast, but the mapping curve cannot adapt to different image histograms
Solution Approach 1:
The patent generates cubic spline curves dynamically based on the histogram information of each image. This allows the mapping curve to adapt to different image characteristics while maintaining efficient processing through mathematical operations on the histogram data.
Solution Approach 2:
The patent changes the parameters of the mapping curve by generating different cubic spline curves based on image-specific histogram information. This parameter adaptation enables the system to handle diverse image content effectively.
3Device complexity
If luminance mapping is applied to all pixels uniformly, then the processing is simple, but specific luminance intervals are not protected
Solution Approach 1:
The patent segments the luminance range into multiple intervals and applies different cubic spline curves to each segment. This ensures that specific luminance intervals are protected and handled with appropriate mapping characteristics while keeping the overall processing manageable.
Solution Approach 2:
The patent applies different mapping characteristics to different luminance intervals through separate cubic spline curves. Each interval receives localized quality treatment optimized for its specific luminance range, preserving important luminance details.
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.