Dynamic Purple Fringe Elimination via Green Channel Correction
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Solution Overview
Problem
Existing methods for eliminating purple fringes in images, such as changing camera or lens structures and using fixed threshold values, are costly, time-consuming, and prone to misjudgments, leading to suboptimal corrections.
Innovation Solution
An image processing system that calculates a dynamic detection threshold value for purple fringes by analyzing pixel hues and using a green channel intensity value to correct red and blue channel intensities within the identified purple fringe regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If camera or lens structure is changed to eliminate purple fringe, then purple fringe elimination effectiveness is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces mechanical/optical structural modifications with a digital image processing system. Instead of changing camera or lens structures to eliminate purple fringe, the invention uses software-based detection and correction algorithms that analyze pixel data, identify purple fringe regions through color space transformation, and correct them through chromatic aberration compensation, thereby eliminating the need for complex mechanical or optical structure changes.
Solution Approach 2:
The patent creates a digital model of the purple fringe phenomenon by transforming image data into different color spaces (RGB to HSV/Lab) and generating virtual representations of color distribution. This digital copying allows the system to analyze and correct purple fringe without physically modifying the optical path or camera structure.
2Ease of operation
If fixed threshold value is used to detect purple fringe region, then detection simplicity is improved, but measurement precision deteriorates
Solution Approach 1:
The patent implements dynamic threshold adjustment based on local image characteristics. Instead of using a fixed threshold value for detecting purple fringe regions, the system calculates adaptive thresholds by analyzing the distribution of color values in different regions of the image. This allows the detection sensitivity to automatically adjust according to the specific image content, lighting conditions, and color distribution, thereby improving detection accuracy while maintaining operational simplicity.
Solution Approach 2:
The patent changes the parameter used for detection from a fixed threshold to a dynamically calculated threshold based on image statistics. The system computes thresholds by analyzing the histogram distribution of color values in the image, transforming the static detection parameter into a dynamic one that adapts to different imaging conditions, thus improving measurement precision without significantly increasing operational complexity.
3Area of stationary object
If threshold range is large, then purple fringe detection coverage is improved, but manufacturing precision deteriorates due to real pixel removal
Solution Approach 1:
The patent applies different processing strategies to different regions of the image based on local characteristics. Instead of uniformly applying a large threshold range across the entire image, the system analyzes local color distribution and adjusts the detection parameters for each region. This allows comprehensive coverage of purple fringe areas while preserving genuine image details, as the local quality of each pixel is evaluated individually rather than using a blanket threshold approach.
4Manufacturing precision
If threshold range is small, then pixel preservation is improved, but purple fringe detection completeness deteriorates
Solution Approach 1:
The patent segments the image processing into multiple stages: initial broad detection to identify potential purple fringe regions, followed by refined analysis to distinguish actual purple fringe from genuine image content. This multi-stage segmentation allows the system to first cast a wide net for detection completeness, then progressively narrow down to preserve only the pixels that are truly part of the purple fringe phenomenon, solving the contradiction between detection completeness and pixel preservation.
Data Source
Figure 1~2
AI summary
Disclosed in the present invention are an image purple fringe eliminating system, method, a computer-readable storage medium, and a photographing device. The system traverses an image, calculates a hue of a pixel, counts a ratio of purple hue to adjacent purple hue pixels in the image, and calculates a dynamic purple fringe detection threshold; creates a mask with the same size as the image acquired by an image acquisition module, and detects the pixels that fall into a purple fringe area; corrects the detected pixel falling into the purple fringe area, correcting both a red channel intensity value and a blue channel intensity value of the pixels within the purple fringe region using a green channel intensity value. The invention can automatically correct the purple fringe of the image, improve the image shooting quality and the user experience.