Perceptual GSDF Image Transcoding Across HDR and SDR Displays
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Solution Overview
Problem
Existing image display technologies struggle to accurately render high dynamic range (HDR) images on standard dynamic range (SDR) displays due to mismatch between perceptual nonlinearity of human vision and fixed spatial frequency encoding, leading to visible artifacts like banding and contour distortion.
Innovation Solution
A reference gray scale display function (GSDF) is generated based on a contrast sensitivity function (CSF) model to determine just noticeable differences (JNDs), allowing for optimal encoding and decoding of image data across displays with varying capabilities, minimizing perceptual errors and artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed spatial frequency encoding is used for image data, then device complexity is reduced, but perceptual accuracy deteriorates due to mismatch with human vision nonlinearity
Solution Approach 1:
The patent applies parameter changes by transforming the encoding from fixed spatial frequency to perceptual nonlinearity-based encoding. The gray scale display function (GSDF) dynamically adjusts code word distribution based on human visual perception characteristics, mapping luminance values according to the contrast sensitivity function (CSF) rather than using uniform spacing. This resolves the contradiction by changing the encoding parameters to match human perception while maintaining manageable system complexity.
Solution Approach 2:
The patent introduces a reference GSDF as an intermediary between the image data and the display device. This intermediary component translates fixed spatial frequency encoded data into perceptually accurate representations by incorporating human vision characteristics. The GSDF acts as a mediator that bridges the gap between simple encoding and perceptual accuracy without requiring complex display hardware modifications.
2Adaptability or versatility
If HDR images are rendered on SDR displays, then display versatility is improved, but image quality deteriorates due to visible artifacts like banding and contour distortion
Solution Approach 1:
The patent achieves universality by creating a reference GSDF that can be applied across different display types (SDR, HDR, mobile devices, televisions). The perceptual nonlinearity-based encoding provides a universal solution that adapts to various display capabilities while maintaining image quality. The GSDF serves multiple functions: it enables HDR content compatibility, reduces artifacts, and works across different device classes without requiring device-specific processing.
Solution Approach 2:
The patent uses parameter changes by adjusting the code word distribution according to the reference GSDF, which is derived from the contrast sensitivity function. This dynamic parameter adjustment allows the same encoded image data to be displayed accurately on different device types by changing how luminance values are mapped to code words, thereby maintaining image quality across diverse display capabilities.
3Device complexity
If code words are evenly distributed across luminance range, then device complexity is reduced, but perceptual accuracy worsens due to non-uniform human vision sensitivity
Solution Approach 1:
The patent applies parameter changes by transforming uniform code word distribution into non-uniform distribution based on the reference GSDF. The encoding adjusts the spacing between code words according to human visual sensitivity, placing more code words in regions where human vision is more sensitive (mid-tone ranges) and fewer code words in less sensitive regions (extreme brightness). This resolves the contradiction by changing encoding parameters to match perceptual requirements.
Solution Approach 2:
The patent implements local quality by applying different code word densities to different luminance regions based on human visual sensitivity characteristics. Rather than uniform distribution, the encoding adapts locally to the contrast sensitivity function, providing finer granularity where human vision is most sensitive and coarser granularity where sensitivity is lower. This localized adaptation maintains perceptual accuracy while managing overall encoding complexity.
Data Source
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AI summary
A handheld imaging device has a data receiver that is configured to receive reference encoded image data. The data includes reference code values, which are encoded by an external coding system. The reference code values represent reference gray levels, which are being selected using a reference grayscale display function that is based on perceptual non-linearity of human vision adapted at different light levels to spatial frequencies. The imaging device also has a data converter that is configured to access a code mapping between the reference code values and device-specific code values of the imaging device. The device-specific code values are configured to produce gray levels that are specific to the imaging device. Based on the code mapping, the data converter is configured to transcode the reference encoded image data into device-specific image data, which is encoded with the device-specific code values.