Bayer Mask Image Decoding with Slope-Adaptive Interpolation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing Bayer mask decoders suffer from cross-color and 'barber's pole' artefacts, particularly on the sparsely sampled red and blue components, despite advancements in non-adaptive linear filters and slope adaptive filters.
Innovation Solution
A method and apparatus that utilize a two-dimensional filter to generate a full-resolution grid of green samples, followed by color difference signal processing, slope and activity calculation, and directional filtering to produce decoded red and blue signals, incorporating a slope index for steered interpolation and a slope consistency measure to reduce artefacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If basic Bayer mask decoders are used, then decoding simplicity is maintained, but cross-color and barber's pole artefacts occur
Solution Approach 1:
The patent implements adaptive filtering where filter parameters dynamically adjust based on local image characteristics. The slope measure and activity measure allow the decoder to adapt its behavior to different regions, switching between different filtering strategies to minimize artifacts while maintaining decoding effectiveness.
Solution Approach 2:
The patent changes filtering parameters based on local image properties. By computing slope measures and activity measures, the system adjusts filter strength and type according to local gradient characteristics, thereby reducing artifacts in different regions without requiring a completely complex decoder architecture.
2Measurement precision
If non-adaptive linear filters are used for decoding, then green component decoding performance is improved, but cross-color artefacts increase on red and blue components
Solution Approach 1:
The patent applies different filtering strategies to different color components based on their sampling characteristics. Green components receive non-adaptive linear filtering to maintain decoding accuracy, while red and blue components receive adaptive filtering based on slope and activity measures to prevent cross-color artifacts.
Solution Approach 2:
The patent dynamically adjusts filtering parameters for red and blue components based on local image characteristics computed from the green component. By using slope measures and activity measures, the system adapts the filtering strength to prevent cross-color artifacts while preserving the benefits of linear filtering for the green component.
3Object-generated harmful factors
If slope adaptive filters are used, then artefact reduction is achieved, but computational complexity and processing time increase
Solution Approach 1:
The patent computes slope measures and activity measures selectively rather than for all pixels. By applying adaptive filtering only where needed based on local gradient characteristics, the system reduces artifacts without requiring full computational processing across the entire image, thereby reducing processing time.
Data Source
Figure 1
Figure 2
Figure 3~5
AI summary
A Bayer-mask image is decoded by forming a decoded green array; calculating a slope at each pixel of the array, expressed as an angle; calculating an activity at each pixel; converting the slope angle and the activity into a complex number for each pixel, of modulus equal to the activity and argument equal to twice the slope angle; expressing said complex numbers in Cartesian coordinates to form a Cartesian slope signal and filtering the Cartesian slope signal with a linear spatial filter to derive a slope measure. Blue - green and red-green values are calculated and interpolated using a slope-adaptive interpolation filter steered by said slope measure.