Image Saturation Adjustment via Local Brightness Deviation
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Solution Overview
Problem
Conventional methods for adjusting image contrast and saturation on electronic devices are inefficient, as they rely on statistical calculations and table lookups, which do not effectively utilize brightness differences between pixels to enhance image quality.
Innovation Solution
A method that calculates a deviation level based on brightness differences between a pixel and its vicinity, using this level to adjust saturation and contrast by applying a global and local gain to modify pixel values, thereby enhancing image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional statistical calculations and table lookups are used to adjust contrast and saturation, then the adjustment process is simple to implement, but the image quality enhancement is insufficient
Solution Approach 1:
The patent applies local quality by calculating deviation levels for individual pixels based on their local brightness characteristics relative to neighboring pixels. Each pixel's saturation and contrast are adjusted independently based on its specific deviation level, allowing different regions of the image to have different adjustment characteristics. This localised approach significantly improves image quality by preserving local details and avoiding uniform over-processing, while the automated calculation process keeps implementation complexity manageable.
Solution Approach 2:
The patent changes the adjustment parameters from global statistical values to local deviation-based values. By calculating deviation levels that reflect local brightness relationships and using these to dynamically determine adjustment factors, the system achieves superior image quality enhancement. The parameter transformation from global statistics to local characteristics enables more precise control over saturation and contrast adjustments.
2Measurement precision
If global statistical data is used for adjustment, then the processing speed is fast, but the precision of saturation and contrast adjustment is insufficient
Solution Approach 1:
The patent segments the image processing into individual pixel-level operations based on local brightness characteristics. Instead of applying a single global adjustment factor to the entire image, the system divides the adjustment process into pixel-specific operations where each pixel's deviation level is calculated and applied independently. This segmentation enables precise local adjustment while maintaining processing efficiency through systematic calculation methods.
Solution Approach 2:
The patent performs preliminary calculation of deviation levels for all pixels before applying the final saturation and contrast adjustments. By pre-calculating the deviation levels based on local brightness relationships, the system prepares the adjustment factors in advance, which streamlines the subsequent adjustment process. This preliminary action ensures both high precision in adjustment and maintained processing speed.
3Manufacturing precision
If conventional adjustment methods are used, then the implementation is straightforward, but the user experience and image quality are not optimized
Solution Approach 1:
The patent implements self-service by automatically calculating deviation levels and determining adjustment factors without requiring manual user input for each pixel or region. The system autonomously analyzes local brightness characteristics, computes deviation levels, and applies appropriate saturation and contrast adjustments. This self-service approach maintains ease of operation while dramatically improving image quality, as the system performs complex local analysis automatically without increasing user burden.
Data Source
AI summary
A method for adjusting saturation of an area of an image is disclosed. The method includes calculating a deviation level of a pixel in the area of the image and calculating a modified saturation value of the pixel in the area of the image according to the deviation level of the pixel in the area of the image and an original saturation value of the pixel in the area of the image. The deviation level indicates brightness differences of the brightness values among the pixel and a pixel set in a vicinity of the pixel in the area of the image. The pixel set includes pixels in the vicinity of the pixel of the area of the image.