Raw Scaler Chromatic Aberration Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional image processing techniques struggle to effectively address image distortions and errors introduced by imaging device components, such as defective pixels, lens imperfections, and sensor noise, leading to inefficient processing and loss of image information.
Innovation Solution
The use of raw scaler logic in an image signal processor to down-scale raw image data, correct chromatic aberrations, and apply filtering coefficients to improve image quality and reduce noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional image processing techniques are used to address image distortions and errors, then processing can be performed, but image information is lost and processing efficiency is reduced
Solution Approach 1:
The patent applies chromatic aberration correction in the raw domain before demosaicing and other processing steps. By correcting the chromatic aberration early in the processing pipeline, the patent prevents information loss that would occur if correction were applied later, while maintaining processing efficiency through optimized raw domain operations.
Solution Approach 2:
The patent separates the chromatic aberration correction process into distinct components handling different color channels (red, green, blue) with channel-specific offset values. This segmentation allows targeted correction for each color channel while maintaining overall processing efficiency through specialized handling of each component.
2Manufacturing precision
If chromatic aberration correction is applied in the raw domain, then image quality is improved and information is preserved, but processing complexity increases
Solution Approach 1:
The patent applies simple parameter adjustments (chromatic offset values for each color channel) to correct chromatic aberration in the raw domain. By modifying only the position parameters of color channels rather than implementing complex transformation algorithms, the patent improves image quality while minimizing increases in processing complexity.
Solution Approach 2:
The patent replaces complex mechanical/optical correction systems with digital signal processing operations in the raw domain. By using computational methods to adjust color channel positions through parameter modifications, the patent achieves high image quality without the complexity of hardware-based correction systems.
3Productivity
If down-scaling is applied to reduce image data size, then processing efficiency is improved, but image detail and quality may be reduced
Solution Approach 1:
The patent applies chromatic aberration correction before down-scaling operations. By correcting the chromatic aberration in the raw, full-resolution data first, the patent ensures that the maximum amount of image information is preserved and corrected before any reduction in data size occurs, thereby maintaining image quality while still achieving processing efficiency benefits from down-scaling.
Data Source
AI summary
Systems and methods for down-scaling are provided. In one example, a method for processing image data includes determining a plurality of output pixel locations using a position value stored by a position register, using the current position value to select a center input pixel from the image data and selecting an index value, selecting a set of input pixels adjacent to the center input pixel, selecting a set of filtering coefficients from a filter coefficient lookup table using the index value, filtering the set of source input pixels to apply a respective one of the set of filtering coefficients to each of the set of source input pixels to determine an output value for the current output pixel at the current position value, and correcting chromatic aberrations in the set of source input pixels.