Aerial Image Artifact Removal via False-Color Composite Analysis
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Solution Overview
Problem
Aerial images often contain atmospheric artifacts like clouds and their shadows, which are difficult to detect and remove, leading to obscured ground features, particularly challenging for remote sensing applications in forestry and other fields.
Innovation Solution
A computer system processes temporally displaced aerial images by creating a false-color composite image, analyzing pixel colors to distinguish clear pixels from cloud and shadow regions, and generating an artifact-free output image by combining clear pixels from multiple input images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud shadows are removed using traditional image processing methods, then cloud artifacts can be eliminated, but shadow regions are mistakenly identified as densely growing forests and cannot be accurately detected
Solution Approach 1:
The patent transitions from analyzing single-band grayscale images to using false-color composite images that combine multiple spectral bands (red, green, blue) to create a new dimensional representation. This allows cloud shadows to be distinguished from forest regions through their characteristic color signatures in the composite image, resolving the detection ambiguity that exists in traditional single-band processing
Solution Approach 2:
The patent applies false-color composite imaging to transform the visual characteristics of cloud shadows and forest regions. By assigning specific spectral bands to color channels and analyzing the resulting color properties, the system can identify cloud shadows through their distinctive color patterns, which differ from the color signature of actual forest vegetation
2Reliability
If multiple temporally displaced images are processed to remove artifacts, then artifact-free images can be generated, but the processing complexity and computational requirements increase
Solution Approach 1:
The patent changes the temporal parameter by processing multiple images taken at different times of the same region. By comparing how artifacts (clouds and shadows) move or disappear across time-displaced images while ground features remain stationary, the system can identify and remove artifacts through temporal variation analysis, improving output quality without requiring complex spatial processing
Data Source
AI summary
A computer system for creating artifact-free aerial images of a region of interest. A computer system receives one or more input aerial images that are obtained at different times. A false-color image is created by applying two or more of the input aerial images to different color channel inputs of the false-color image. Based on the color of the pixels in the false-color image, pixels in the two or more input aerial images are classified as representing clear, cloud or shadow areas. An output image is created by combining pixels that are classified as representing clear areas from two or more of the input aerial images.