Dynamic Range Correction for Image Content
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Solution Overview
Problem
Current digital image technologies suffer from limited dynamic range, resulting in loss of detail in both dark and bright portions of images due to the limited contrast ratios of image sensors and display devices, which conventional exposure adjustments and dynamic range compression methods fail to adequately address.
Innovation Solution
A dynamic range correction technique that identifies and prioritizes important image content, such as faces, by adjusting exposure and applying specific gain adjustments based on the location and type of content, using a combination of object detection units, gain lookup tables, and nonlinear filtering to enhance local contrast and prevent color saturation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional dynamic range compression methods are applied to the entire image, then the overall dynamic range is improved, but important local details in critical areas (such as faces) are still lost
Solution Approach 1:
The patent applies different dynamic range correction strengths to different regions of the image based on content importance. Face detection identifies critical regions, and gain lookup tables apply enhanced correction specifically to these regions while using standard correction for other areas, preserving local details where most needed.
Solution Approach 2:
The image is segmented into important content regions (detected faces) and non-important regions. Different processing paths are applied: enhanced dynamic range correction for face regions and standard correction for other regions, allowing optimized information preservation in critical areas.
2Illumination intensity
If exposure time is increased to capture dark areas, then visibility of dark portions is improved, but bright areas become overexposed and lose detail
Solution Approach 1:
The system applies spatially varying gain adjustments based on detected content. Faces in dark regions receive enhanced brightness through targeted gain application from lookup tables, while bright regions maintain their exposure levels, preventing overexposure while improving visibility of important dark areas.
Solution Approach 2:
Gain lookup tables serve as an intermediary mechanism that applies selective brightness enhancement. The lookup tables store pre-computed gain values that are applied specifically to pixels in detected face regions, mediating between the need for dark area enhancement and bright area preservation without direct exposure time adjustment.
3Stability of the object's composition
If dynamic range compression is applied uniformly across the image, then the contrast ratio is improved, but local contrast in important regions is not sufficiently enhanced
Solution Approach 1:
The patent implements region-specific dynamic range correction where face regions receive enhanced local contrast enhancement through targeted gain application. The correction strength varies spatially, with higher enhancement applied to detected faces and standard enhancement elsewhere, preserving local detail visibility in critical regions while maintaining overall contrast stability.
Data Source
AI summary
Disclosed are method and a corresponding apparatus, where the method according to one embodiment includes making a determination that a first portion of digital image data represents a physical object of a predetermined type, determining an amount of a parameter, such as a gain, to apply to the first portion of the digital image data, based on the determination that the first portion of the digital image data represents a physical object of the predetermined type, and applying the determined amount of the parameter to the first portion of the digital image data. The method may be part of a dynamic range correction operation.