Bayer-Consistent Raw Image Scaling with Directional Filtering
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Solution Overview
Problem
Existing methods for raw domain image scaling face challenges in maintaining Bayer consistency and achieving high image quality, especially when scaling by different factors in horizontal and vertical directions, leading to image artifacts and increased complexity.
Innovation Solution
A Bayer-consistent ruleset is applied, using filter weights concentrated within color sub-tiles and ensuring the center of gravity of filter weights coincides with the geometric pixel center, to produce high-quality scaled images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If raw domain scaling is performed using existing methods, then processing load is reduced and power consumption decreases, but Bayer consistency is lost and image quality deteriorates
Solution Approach 1:
The patent divides the input pixel array into multiple sub-arrays corresponding to different color channels (red, green, blue) and processes each sub-array independently through separate filtering operations. This segmentation allows the system to maintain Bayer consistency by ensuring that pixels of the same color are properly aggregated while reducing the computational complexity for each individual processing block, thus lowering power consumption.
Solution Approach 2:
The patent applies different filtering operations tailored to each color channel's specific characteristics. Each color sub-array receives a filtering operation optimized for its local properties (e.g., red pixel aggregation, green pixel aggregation, blue pixel aggregation), which maintains the local Bayer pattern quality while enabling efficient processing that reduces overall power consumption.
2Productivity
If raw domain scaling is performed using existing methods, then processing load is reduced, but image quality and resolution are compromised
Solution Approach 1:
The patent performs filtering operations on the raw pixel data before the scaling operation. By pre-filtering each color sub-array to aggregate neighboring pixels of the same color, the system prepares the data in advance to maintain high image quality during the subsequent scaling process, avoiding the need for complex post-processing that would increase computational load.
Solution Approach 2:
The patent changes the processing parameters by applying different filtering kernels and aggregation methods for each color channel based on its specific requirements. This parameter optimization allows the system to maintain high image quality and resolution while processing data more efficiently, as each channel is handled with parameters tuned to its characteristics rather than using a uniform approach.
3Adaptability or versatility
If scaling is performed with different horizontal and vertical scaling factors, then aspect ratio conversion is achieved, but Bayer consistency and image quality are compromised
Solution Approach 1:
The patent segments the pixel array into color-specific sub-arrays and applies independent filtering and scaling operations to each. This segmentation enables the system to handle different horizontal and vertical scaling factors for each color channel separately, maintaining Bayer consistency during aspect ratio conversion while achieving the desired versatility in output format.
Solution Approach 2:
The patent implements a dynamic processing approach where the filtering and scaling operations adapt to the specific scaling factors required for different output aspect ratios. The system can dynamically adjust the filtering kernel sizes and aggregation methods based on the desired output format, maintaining Bayer consistency while providing versatile aspect ratio conversion capabilities.
Data Source
AI summary
A system and method for scaling an image includes receiving raw image data comprising input pixel values which correspond to pixels of an image sensor; and filtering pixels according to a Bayer-consistent ruleset by a first scaling factor in a first direction and a second scaling factor in a second direction perpendicular to the first direction, wherein the first scaling factor is different from the second scaling factor. The system and method may also include outputting scaled image data as output pixel values, which correspond to subgroups of the input pixel values. The Bayer-consistent ruleset includes a set of filter weights and a series of scaling rules. The Bayer-consistent ruleset results in a scaled image having a high degree of Bayer-consistency.