Multi-Band Image Processing Using Gradient Weighting
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Solution Overview
Problem
Existing image processing systems fail to effectively reflect important information from individual bands when composing a single image from multiple sensor-acquired images, as they calculate the structure tensor based on a total sum of gradients without considering band characteristics.
Innovation Solution
An image processing system that determines the importance of each band using a weight calculation method, restricts the gradient of the output image based on these weights, and optimizes the image composition to include gradient information from each band, using a band weight determination unit, gradient restriction calculation unit, and image optimization unit.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the structure tensor is calculated based on a total sum of gradients without considering band characteristics, then the calculation process is simple, but important information contained in a particular band is not reflected on the output image
Solution Approach 1:
The patent applies local quality by introducing band-specific weights to the structure tensor calculation. Instead of treating all bands uniformly with a total sum of gradients, each band is assigned a weight that reflects its importance characteristics. This allows different parts of the multi-band image data to have different levels of influence on the output image, preserving important information from specific bands while maintaining a manageable calculation process.
2Loss of information
If band weights are introduced to reflect important information from each band, then the output image contains more important information, but the calculation complexity increases
Solution Approach 1:
The patent employs parameter changes by introducing weight parameters for each band in the structure tensor calculation. These weights are determined based on band importance characteristics and are used to modulate the contribution of each band's gradient information. This parameter-based approach allows the system to preserve important information from specific bands while controlling calculation complexity through the use of scalar weight factors rather than complex band-specific processing.
3Measurement precision
If gradient restriction is applied using band weights, then the output image gradient reflects important band information, but the processing time increases
Solution Approach 1:
The patent applies preliminary action by determining the band weights before performing the gradient restriction calculation. The weight determination is performed once based on band importance characteristics, and these pre-calculated weights are then used in the structure tensor computation. This preliminary weighting step avoids the need for iterative or repeated weight calculations during gradient restriction, thereby improving processing efficiency while maintaining gradient accuracy that reflects important band information.
Data Source
AI summary
An image processing system includes: a weight determination circuitry configured to determine a band containing important information from among a group of images, which are acquired by a plurality of sensors, and to express a degree of importance of the band as a weight; a calculation circuitry configured to calculate, using the weight, an amount calculated based on a gradient of an image based on a gradient of each image, that is calculated based on the group of images, in order to restrict a gradient of an output image; and an image optimization circuitry configured to compose the output image using the amount calculated based on the gradient of the image.