Spherical Image Auto Exposure to Reduce Stitch-Line Variation
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Solution Overview
Problem
Conventional auto exposure processing for spherical images using separate front and rear image sensors results in visible local exposure variation along the stitch line due to differing exposure levels, leading to poor image quality and dynamic range.
Innovation Solution
Implementing pre- or post-processing techniques to determine an average global luminance value, calculate delta luminance values, and update auto exposure configurations for each sensor to minimize exposure variation, ensuring consistent luminance across the spherical image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate auto exposure processing is applied to front and rear image sensors, then each sensor can be optimized for its specific field of view, but visible local exposure variation occurs along the stitch line
Solution Approach 1:
The patent applies different exposure processing strategies to different regions of the spherical image. Specifically, it identifies a stitch line region where front and rear hemisphere images are joined and applies specialized exposure adjustment algorithms to this local region to minimize visible variations, while allowing other regions to maintain their sensor-specific exposure optimization.
Solution Approach 2:
The patent dynamically adjusts exposure parameters (such as gain, exposure time, or brightness compensation) based on the location of pixels relative to the stitch line. By changing these parameters locally at the stitch line region versus other regions, the system resolves the contradiction between sensor-specific optimization and exposure consistency.
2Manufacturing precision
If exposure levels are equalized across all sensors, then consistency is improved, but dynamic range and image quality deteriorate
Solution Approach 1:
Instead of applying uniform exposure equalization across the entire spherical image, the patent applies localized exposure adjustment only to the stitch line region where inconsistencies are most visible. This allows the majority of the image to maintain its original sensor-optimized exposure characteristics and dynamic range, while only correcting the problematic transition zone.
Solution Approach 2:
The patent applies exposure adjustment selectively rather than universally. By applying correction only where necessary (at the stitch line) and not across the entire image, it avoids the excessive action that would degrade overall image quality and dynamic range while still achieving the needed consistency at critical transition points.
Data Source
AI summary
Auto exposure processing for spherical images improves image quality by reducing visible exposure level variation along a stitch line within a spherical image. An average global luminance value is determined based on luminance values determined for first and second images, which are based on auto exposure configurations of first and second image sensors used to obtain those first and second images. Delta luminance values are determined for the first and second images using the average global luminance value. The first and second images are then updated using the delta luminance values, and the updated first and second images are used to produce a spherical image.