HDR Image Signal Conversion Curve for Stripe-Noise-Free Quantization
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Solution Overview
Problem
Current HDR image processing methods suffer from stripe noise due to inadequate quantization quality, particularly when brightness values below 0.1 nits exceed the Schreiber threshold, leading to suboptimal display quality.
Innovation Solution
A method and apparatus for processing image signal conversion using an optical-electro transfer function with specific rational number parameters (a, b, m, p) to control the conversion characteristic curve, improving quantization quality by expanding the dynamic range and reducing stripe noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If linear quantization is directly performed on HDR video, then the encoding process is simple, but information of the HDR source is severely damaged
Solution Approach 1:
The patent applies a transfer function to transform the HDR video parameters from linear space to non-linear space before quantization. This parameter transformation allows the video data to better represent human visual perception characteristics, enabling effective quantization while preserving HDR information without requiring complex encoding processes.
Solution Approach 2:
The transfer function serves as an intermediary between the HDR source and the quantization process. It acts as a mediator that transforms the data into a form suitable for quantization while preserving the essential information, avoiding both information loss and overly complex encoding.
2Ease of operation
If conventional optical-electro transfer function is used, then the processing is straightforward, but Weber scores exceed the Schreiber threshold causing perceivable stripe noise
Solution Approach 1:
The patent modifies the transfer function parameters (specifically using a rational function with parameters a, b, m, and p) to optimize the transformation curve. This parameter adjustment ensures that the Weber scores remain below the Schreiber threshold across the entire brightness range, eliminating perceivable stripe noise while maintaining processing simplicity.
Solution Approach 2:
The transfer function dynamically adapts the transformation based on the input brightness values, using different slopes and curves for different brightness ranges. This dynamic behavior allows the system to maintain optimal quantization quality across varying brightness levels without introducing stripe noise.
3Manufacturing precision
If brightness segment protection is prioritized through non-linear transfer, then quantization quality improves, but the dynamic range coverage is reduced
Solution Approach 1:
The transfer function applies different transformation characteristics to different brightness segments. It provides enhanced protection and higher quantization quality for key brightness segments (particularly mid-tones and shadows) while maintaining adequate coverage for highlights, achieving local optimization without sacrificing overall dynamic range.
Solution Approach 2:
The transfer function effectively segments the brightness range into different regions with different transformation characteristics. This segmentation allows prioritized protection of important brightness segments while maintaining overall dynamic range coverage, resolving the contradiction between quality and coverage.
Data Source
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AI summary
Embodiments of the present invention disclose a method and an apparatus for processing image signal conversion, and a terminal device. The method includes: obtaining an input primary color signal, where the primary color signal is a numeric value of an optical signal corresponding to an image, and the primary color signal is proportional to light intensity; and performing conversion processing on the primary color signal, to obtain processed image information, where the image information is a numeric expression value of the image, and the conversion processing includes at least the following processing: L′=apLp−1L+1m+b, where a, b, m, and p are rational numbers, L is the input primary color signal, and L' is the image information generated after conversion processing. When the embodiments of the present invention are used, quantization quality can be improved.