Image Processing Apparatus Correcting Atmospheric Turbulence Fluctuations
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Solution Overview
Problem
Existing image processing techniques fail to effectively correct long-period fluctuations in video images caused by atmospheric turbulence, especially when moving objects are present, leading to deteriorated image quality and erroneous detection in monitoring systems.
Innovation Solution
An image processing apparatus that acquires and processes multiple frames of data to calculate displacement between reference and target images, determines moving object regions, and interpolates displacement data to correct for long-period fluctuations, ensuring accurate alignment and image stabilization without breaking up moving objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If fluctuation correction is performed using only temporally neighboring images to avoid breaking moving objects, then moving object integrity is preserved, but long-period fluctuations cannot be corrected
Solution Approach 1:
The patent segments the image sequence into multiple groups, where each group contains temporally neighboring images used for correcting short-period fluctuations. By processing different groups with different temporal spans, the system can correct both short-period and long-period fluctuations while preserving moving object integrity within each group.
Solution Approach 2:
The patent introduces a new dimension of temporal grouping by organizing images into multiple groups with different temporal spans. This allows the system to apply different correction strategies to different groups, effectively separating the correction of short-period and long-period fluctuations in the temporal dimension.
2Manufacturing precision
If multiple temporally distant images are used for fluctuation correction, then long-period fluctuations can be corrected, but moving objects are broken up due to motion
Solution Approach 1:
The patent divides the image sequence into multiple groups, with each group containing images within a specific temporal span suitable for motion compensation. By segmenting the correction process into group-level operations, the system can handle long-period fluctuations across groups while maintaining object integrity within each group's temporal window.
Solution Approach 2:
The patent dynamically adjusts the temporal span of image groups based on the correction needs. Different groups use different temporal spans - shorter spans for regions with moving objects and longer spans for regions with long-period fluctuations, allowing the system to adapt to local requirements.
3Manufacturing precision
If image averaging is performed to correct atmospheric turbulence fluctuations, then image quality improves, but moving objects become blurred due to motion
Solution Approach 1:
The patent segments the correction process into group-level operations, where images within each group are processed together. This segmentation allows motion compensation to be applied at the group level, preventing the blurring that occurs when averaging images across different temporal spans without proper motion alignment.
Solution Approach 2:
The patent performs motion compensation as a preliminary action before averaging images within each group. By aligning images based on detected motion vectors before the averaging process, the system prevents moving objects from becoming blurred while still achieving the noise reduction benefits of averaging.
Data Source
AI summary
An image processing apparatus includes an acquisition unit, first and second correction units, first and second calculation units, and a determination unit. The acquisition unit acquires image data pieces obtained by temporally successively capturing images of an object. The first correction unit acquires first correction data by performing fluctuation correction on processing target image data using temporally neighboring image data pieces among the acquired image data pieces. The first calculation unit calculates, as first displacement data, an amount of displacement between reference and the processing target image data or the first correction data. The determination unit determines a moving object region. The second calculation unit calculates second displacement data by interpolating the first displacement data in the determined moving object region based on the first displacement data or the first correction data. The second correction unit corrects based on the second displacement data to obtain second correction data.