Adaptive Lens Shading Correction Through Scene-Aware Block Analysis
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Solution Overview
Problem
Conventional lens shading correction technologies face misjudgment due to differences among imaging modules, leading to shading compensation errors and hardware limitations, especially in scenes with varying color temperatures, and require additional computation and hardware resources.
Innovation Solution
A method for adaptively correcting image shadow by dividing images into blocks, filtering similar blocks based on hue, luminance, saturation, and sharpness differences, calculating color channel differences, and adjusting shading rates using a moving average filtering scheme to compensate for lens shading without additional computation or hardware, while dynamically updating the shading rate for scene changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional lens shading correction is applied, then shading compensation is achieved, but misjudgment occurs due to differences among imaging modules and metamerism errors in varying color temperature scenes
Solution Approach 1:
The patent implements dynamic shading correction by continuously monitoring scene color temperature and adapting the correction algorithm parameters in real-time. The system dynamically adjusts the shading compensation based on detected scene characteristics, enabling it to handle varying color temperatures and different imaging modules effectively, thereby resolving the contradiction between measurement precision and adaptability
Solution Approach 2:
The patent changes key parameters including color temperature detection thresholds, shading rate calculation weights, and block similarity criteria based on scene conditions. By dynamically adjusting these parameters, the system maintains high shading compensation accuracy across different imaging modules and lighting conditions while avoiding metamerism errors
2Measurement precision
If pixel-level operations are performed for shading compensation, then comprehensive correction across all color channels is achieved, but large computing power is consumed
Solution Approach 1:
The patent segments the image into multiple blocks and processes each block independently to calculate shading rates. This segmentation approach allows comprehensive correction across all color channels while reducing computational complexity by limiting operations to local block comparisons rather than global pixel-level operations across the entire image
Solution Approach 2:
The patent performs shading compensation on representative blocks rather than every single pixel in the image. By calculating shading rates from selected blocks and applying them to corresponding regions, the system achieves comprehensive correction coverage while significantly reducing computational power consumption through partial action
3Productivity
If additional software computing units are used for shading compensation, then real-time correction is achieved, but device complexity increases
Solution Approach 1:
The patent designs a shading correction system that integrates multiple functions into a unified processing pipeline. The same image processing unit that performs basic image processing also handles color temperature detection, block comparison, and shading rate calculation, eliminating the need for separate dedicated hardware units and reducing overall device complexity while maintaining real-time correction capability
Solution Approach 2:
The patent implements a self-service mechanism where the image processing unit automatically detects scene color temperature and adjusts shading correction parameters without external intervention. The system uses existing image data and processing resources to perform self-diagnosis and self-correction, achieving real-time adaptation without adding complex control hardware
Data Source
AI summary
A method for adaptively correcting image shadow and a system are provided. In the method, an image captured through a lens is obtained, and pixel values of different color channels of the image are obtained. The image is divided into multiple blocks, and image differences among the blocks are obtained by counting pixel values of each block, so as to filter out similar blocks. Afterwards, multiple block pairs can be obtained based on a filtering result of the similar blocks. A shading rate of the image can be determined according to difference ratios of color channels of the block pairs. Based on the shading rate, shading correction is performed upon the image. If any change occurs to a scene when the shading correction is performed on continuous images, the shading rate is updated according to difference ratios of red and blue channel values of the block pairs.