Foveated HDR Imaging With Gaze-Based Adaptive Exposure
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing digital imaging systems fail to adapt exposure levels spatially, leading to overexposed or underexposed areas in high dynamic range (HDR) images, which obscures image details.
Innovation Solution
Implementing a gaze tracking system to identify fixation points in HDR images and applying adaptive exposure adjustments using Gaussian masks to enhance pixel intensity, creating foveated images with improved detail in areas of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If uniform exposure is applied to the entire HDR image, then the exposure settings are consistent across all areas, but this results in overexposed or underexposed areas that obscure image details
Solution Approach 1:
The patent applies different exposure settings to different regions of the image based on local characteristics. A Gaussian mask is used to create spatially varying exposure adjustments, where the center region (foveated area) receives different exposure treatment than peripheral regions. This allows optimal exposure for each local area, preserving image details that would otherwise be lost in uniform exposure.
2Loss of information
If spatially adaptive exposure is applied to correct overexposed and underexposed areas, then image detail is preserved, but this requires complex processing that increases computational requirements
Solution Approach 1:
The image is divided into distinct regions using a Gaussian mask, separating the foveated (center) area from peripheral areas. This segmentation allows independent exposure adjustment for each region, simplifying the processing by treating different areas differently rather than attempting complex global optimization. The mask-based approach provides a computationally efficient way to implement spatially adaptive exposure.
3Manufacturing precision
If foveated imaging is used to enhance the fixation point area, then detail in the area of interest is improved, but peripheral areas may lose detail
Solution Approach 1:
The patent dynamically changes exposure parameters based on spatial location and user fixation point. The Gaussian mask creates a smooth transition of exposure parameters from the center (high exposure for detail) to peripheral regions (adjusted exposure to prevent overexposure). This parameter variation preserves detail in both foveated and peripheral areas by optimizing exposure settings for each spatial zone.
Data Source
AI summary
Systems and methods are disclosed that address the need for adaptive exposure within high dynamic range (HDR) images. Solutions can leverage recent advances in the use of virtual reality (VR) headsets and Augmented Reality (AR) displays equipped with infrared (IR) eye tracking devices. A gaze vector determined by the eye tracking device identifies one or more fixation points on the image that corresponds to an area where there exists a faulty exposure. The exposure around the fixation point can be adaptively corrected using image processing techniques. Using spatial adaptive exposure, the resulting image, a type of foveated image, can be rendered on a low dynamic range (LDR) display with sufficient detail.