Smart Binning Circuit EDI and 4-Sum Noise Resolution Trade-off
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Solution Overview
Problem
Current image photographing devices face challenges in achieving high functionality, compact size, reduced weight, and low power consumption while maintaining image resolution, especially under varying illumination conditions.
Innovation Solution
A smart binning circuit that generates a binning value through edge detection interpolation (EDI) and combines it with an average value from a 4-sum binning operation, adjusting weights based on edge information strength to improve resolution and reduce noise, and selectively outputs image data based on illumination conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If 4-sum binning operation is performed to reduce noise, then noise reduction is achieved, but resolution deteriorates
Solution Approach 1:
The patent segments the binning process into two distinct components: traditional 4-sum binning for noise reduction and edge detection interpolation binning for resolution preservation. By separating these functions into parallel processing paths, the system can selectively apply appropriate processing to different image regions, thus achieving both noise reduction and resolution maintenance simultaneously
Solution Approach 2:
The patent dynamically changes the binning processing parameters based on local image characteristics. By detecting edge information and calculating edge strength, the system adjusts the binning mode (4-sum vs. EDI) and interpolation weights according to the specific region's features, optimizing both noise reduction and resolution preservation adaptively
2Measurement precision
If edge detection interpolation binning is performed to preserve resolution, then resolution is maintained, but noise reduction capability decreases
Solution Approach 1:
The patent applies different binning quality characteristics to different local regions of the image. In edge regions, edge detection interpolation binning is applied to preserve sharpness and resolution. In non-edge regions, traditional 4-sum binning is applied to achieve maximum noise reduction. This local differentiation resolves the contradiction by ensuring each region receives the most appropriate processing
Solution Approach 2:
The patent implements a dynamic binning system that automatically switches between different binning modes based on real-time edge detection results. The system dynamically calculates edge strength for each pixel neighborhood and adaptively selects the optimal binning strategy, making the noise reduction and resolution preservation capabilities flexible and context-dependent
3Measurement precision
If smart binning operation is performed to improve resolution, then resolution enhancement is achieved, but processing complexity increases
Solution Approach 1:
The patent performs preliminary edge detection and edge strength calculation before the actual binning operation. By pre-identifying edge regions and determining the appropriate binning mode for each region, the system simplifies the subsequent binning process and avoids complex real-time decision-making during pixel processing, thus reducing overall computational complexity
Solution Approach 2:
The patent designs a universal binning circuit that integrates multiple functions: 4-sum binning, edge detection interpolation binning, edge strength calculation, and adaptive mode selection. By consolidating these functions into a single multi-functional circuit, the patent reduces the need for separate processing units and simplifies the overall system architecture despite the enhanced processing capabilities
Data Source
AI summary
A smart binning circuit includes an edge information generator suitable for generating edge information from pixel data outputted from a pixel array; a weight allocator suitable for allocating a weight based on the edge information; a binning component suitable for generating a binning value by performing an edge detection interpolation (EDI) binning on the edge information; a bayer binning component suitable for generating an average value representing pixels that are down-scaled through a 4-sum binning operation; and a combiner suitable for combining the binning value and the average value according to the allocated weight.