HDR Image Data Structure for Backwards-Compatible Decoding
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Solution Overview
Problem
Conventional digital image formats are unable to efficiently store and reproduce high dynamic range (HDR) images, resulting in large file sizes and compatibility issues with existing image viewers, while existing HDR formats are either proprietary or require specialized software.
Innovation Solution
A data structure comprising a tone map portion and a high dynamic range information portion, along with ratio data, allows legacy image viewers to decode HDR images by using tone map information and ignoring HDR details, while enabling advanced decoders to reconstruct the full HDR image by combining tone map and ratio data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional digital image formats are used to store HDR images, then compatibility with existing image viewers is maintained, but file sizes become prohibitively large and image quality is degraded
Solution Approach 1:
The HDR image data is segmented into two distinct portions: a tone map portion containing tone mapped image data, and a high dynamic range information portion containing HDR-specific data including ratio data. This segmentation allows legacy viewers to process only the tone map portion while advanced viewers can utilize both portions for high-fidelity HDR reproduction, thereby reducing overall file size requirements and improving compatibility.
Solution Approach 2:
A data structure intermediary is introduced that bridges conventional image formats and HDR formats. This data structure contains both tone mapped image data (compatible with legacy viewers) and HDR information (for advanced viewers), acting as a mediator that enables both conventional and HDR-capable systems to process the same image data efficiently.
2Measurement precision
If proprietary RAW formats are used for HDR images, then image quality is preserved, but data storage requirements become excessive and software compatibility is reduced
Solution Approach 1:
The invention extracts only the essential HDR information (ratio data and metadata) from complete proprietary RAW formats, separating it from the full HDR image data. This extraction approach preserves the critical HDR quality information while reducing data storage requirements, as legacy viewers can process the tone mapped portion without needing the complete RAW data structure.
Solution Approach 2:
The data structure is designed to be universal, serving multiple functions: it provides full HDR quality for advanced viewers who can process the complete data structure, while simultaneously providing compatible tone mapped images for legacy viewers. This multi-functionality eliminates the need for separate proprietary formats for different viewing capabilities.
3Measurement precision
If full HDR data is stored for all images, then high-fidelity HDR reproduction is enabled, but processing complexity increases and legacy system compatibility is lost
Solution Approach 1:
The data structure dynamically adapts to different processing capabilities. Advanced decoders that support HDR can utilize the complete data structure including ratio data for high-fidelity reproduction, while legacy decoders automatically process only the tone map portion. This dynamic adaptation allows the system to optimize processing complexity based on the capabilities of the receiving device.
4Adaptability or versatility
If tone mapped images are used for legacy compatibility, then file size is reduced and compatibility is improved, but HDR information is lost
Solution Approach 1:
The tone mapped image data is nested within a larger data structure that also contains HDR information portions. Legacy viewers can process the inner tone map portion while advanced viewers can access the outer container structure to retrieve and process the embedded HDR ratio data and metadata, thereby preserving HDR information without compromising legacy compatibility.
Data Source
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Figure 4A~4B
AI summary
Techniques for high dynamic range image processing are presented. Base layer data, first checksum parameter, and residual ratio data for a high dynamic range (HDR) image are each received. A second checksum parameter is computed for the base layer data based upon the first SOF after the last APP11 marker segment and includes all following bytes up to and including the EOI marker. The first and second checksum parameters are compared to determine if base layer has been altered.