Intra-Plane Inter-Plane Bayer Image Prediction
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Solution Overview
Problem
Bayer color encoding in digital imaging systems relies primarily on intra-plane correlations, which limits encoding efficiency due to the lack of consideration for inter-plane correlations, resulting in suboptimal compression of color image data.
Innovation Solution
The integration of inter-plane correlations with intra-plane correlations during Bayer image encoding and decoding enhances prediction accuracy, allowing for improved coding efficiency by generating residuals through combined prediction methods and entropy coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If only intra-plane correlation is used for prediction, then the encoding process is simple, but the encoding efficiency is limited
Solution Approach 1:
The patent combines intra-plane prediction and inter-plane prediction into a unified prediction framework. The predictor for a pixel at position (x,y) with color component C is computed as: p(x,y,C) = (1-α)×intra_plane_prediction(x,y,C) + α×inter_plane_prediction(x,y,C), where α is a weighting factor. This merging allows the system to exploit both spatial correlations within the same color plane and correlations across different color planes, thereby improving encoding efficiency while maintaining a manageable level of complexity through a systematic combination approach.
2Measurement precision
If inter-plane prediction is added to enhance prediction accuracy, then encoding efficiency improves, but computational complexity increases
Solution Approach 1:
The patent performs preliminary decomposition of the prediction process into distinct intra-plane and inter-plane components. By pre-defining the prediction formulas for each component separately (intra-plane using neighboring pixels of the same color, inter-plane using pixels of different colors), the system enables independent optimization and selective application. This preliminary structuring allows the encoder to compute predictions systematically and apply appropriate weighting without requiring complex real-time decision-making, thus improving prediction accuracy while controlling computational complexity.
3Reliability
If multiple levels of residual computation are performed, then prediction performance is enhanced, but processing time increases
Solution Approach 1:
The patent introduces dynamic adaptability into the prediction process by allowing the encoder to select between different prediction configurations based on image content characteristics. The system can dynamically adjust the weighting factor α between intra-plane and inter-plane predictions, and can choose to apply one or multiple levels of residual computation depending on the specific image region and color component. This dynamic approach enables the system to achieve high prediction performance when needed while reducing processing time for regions where simpler prediction suffices, thus balancing reliability and processing time.
Data Source
AI summary
An apparatus and method for enhanced encoding and decoding of Bayer images is presented. The use of intra-plane prediction, which relies on correlation between neighboring pixels of the same color, is enhanced by adding inter-plane prediction that relies on correlation between neighboring pixels in different color planes (i.e., different colors). The inter-plane prediction is performed within either a single residual computation, or across multiple residual computations, such as generating an intra-predicted set of residuals which are then utilized in computing inter-predicted residuals.