Pixel Saturation Adjustment via Cumulative Distribution Functions
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Solution Overview
Problem
Satellite and aerial images often suffer from under-saturation due to atmospheric conditions, resulting in flat, non-vivid colors, which makes it desirable to adjust pixel saturation levels to match those found in nature.
Innovation Solution
A computer-implemented method and system that access target and input image distribution functions to associate and adjust pixel saturation values, using cumulative distribution functions (CDFs) to transform initial saturation values of input images to target saturation values, thereby normalizing pixel saturation without altering the image's appearance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If satellite and aerial images are taken at higher elevations, then the coverage area increases, but the pixel saturation decreases due to atmospheric conditions
Solution Approach 1:
The patent applies parameter changes by transforming the saturation values of pixels using cumulative distribution functions (CDFs). The system calculates a target CDF from reference images and an input CDF from the input image, then maps pixel saturation values from the input CDF to the target CDF. This mathematical transformation adjusts the saturation parameter of each pixel to match the distribution characteristics of naturally saturated images, thereby resolving the contradiction between coverage area and pixel saturation.
2Ease of manufacture
If pixel saturation is increased to enhance vividness, then color vividness improves, but the natural appearance of the image may be altered
Solution Approach 1:
The patent employs feedback by using cumulative distribution functions to analyze the saturation distribution of pixels in both the input image and reference images. The system calculates the target saturation value for each pixel based on its position in the input CDF and the corresponding value in the target CDF. This feedback mechanism ensures that the saturation adjustment preserves the relative distribution characteristics of the original image while achieving the desired vividness, thus maintaining natural appearance.
Solution Approach 2:
The system changes the saturation parameter of each pixel through mathematical transformation using CDFs. By mapping the cumulative distribution of saturation values from the input image to the target distribution derived from reference images, the patent achieves enhanced color vividness while preserving the natural appearance through statistically rigorous parameter transformation.
Data Source
AI summary
In one aspect, a computer-implemented method for adjusting pixel saturation may generally include accessing, by one or more computing devices, a target distribution function associated with at least one target image and an input distribution function associated with at least one input image. The target distribution function may define a target probability for a pixel saturation of each pixel within the target image(s). The input distribution function may define an input probability for an initial saturation value of each pixel within the input image(s), with the input image(s) differing from the target image(s). The method may also include associating, by the computing device(s), the initial saturation value of each pixel within the input image(s) with a target saturation value based on the input and target distribution functions and adjusting, by the computing device(s), the initial saturation value of each pixel within the input image(s) to the corresponding target saturation value.