Pixel Value Grouping for Consistent Image Processing
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Solution Overview
Problem
Image processing systems in camera pipelines face challenges with inconsistent edge detection across processing modules, difficulty in handling multiple edges within a kernel, and balancing contradictory processing functions like denoising and sharpening, which leads to artefacts and tuning issues.
Innovation Solution
An image processing system that groups pixel values into multiple clusters using a clustering algorithm, allowing for consistent classification and processing of pixel values based on defined groups, enabling consolidated operations for multiple functions like defective pixel detection, correction, denoising, sharpening, and de-mosaicing, and storing group indication data for efficient real-time processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple separate processing modules are used for different image processing functions, then each function can be processed independently, but processing time increases and latency increases
Solution Approach 1:
The patent combines multiple separate processing modules (defective pixel detection, denoising, sharpening, de-mosaicing) into a single integrated processing module that performs all functions in one pass through the pixel data stream, eliminating the need to reprocess pixels multiple times and significantly reducing latency
Solution Approach 2:
The integrated processing module is designed to perform multiple image processing functions simultaneously using a unified approach based on pixel value classification, allowing a single module to handle defective pixel detection, denoising, sharpening, and de-mosaicing operations
2Adaptability or versatility
If multiple separate processing modules are used for different image processing functions, then each function can be optimized independently, but the system complexity increases
Solution Approach 1:
The patent employs a universal processing module that handles multiple image processing functions through a single unified algorithm based on pixel value classification and grouping, reducing system complexity while maintaining the ability to perform defective pixel detection, denoising, sharpening, and de-mosaicing operations
Solution Approach 2:
The processing module dynamically adjusts processing parameters and group definitions based on the specific function being performed and the characteristics of the input pixel data, allowing flexible optimization of different processing functions within a single unified framework
3Reliability
If traditional edge detection methods are used in each processing module, then edges can be detected, but inconsistent edge detection occurs across different modules
Solution Approach 1:
The patent merges edge detection functionality into the unified pixel value classification approach used across all processing functions, ensuring that edges are consistently identified and handled the same way regardless of which processing function is being applied, thereby eliminating inconsistent edge detection and associated artifacts
Solution Approach 2:
The processing module performs preliminary classification of pixel values into groups based on their characteristics before applying any specific processing function, ensuring that all subsequent operations (including edge detection, denoising, sharpening) work with consistently classified data, which prevents edge-related artifacts
4Manufacturing precision
If denoising and sharpening are applied separately in different modules, then each function can be optimized, but contradictory processing leads to artifacts
Solution Approach 1:
The patent combines denoising and sharpening operations into a single integrated processing sequence within the unified module, where pixel values are first classified into groups, then denoised by replacing values with group averages, and finally sharpened by comparing original and denoised values, ensuring consistent and artifact-free processing
Solution Approach 2:
The processing module performs preliminary classification of pixel values into homogeneous groups before applying denoising operations, ensuring that denoising only occurs within regions of similar pixel values and does not affect edges, while subsequent sharpening operations can then safely enhance edges without creating artifacts
Data Source
AI summary
Data processing systems (e.g. image processing systems) and methods are provided for processing a stream of data values (e.g. pixel values). The image processing system comprises a processing module configured to: receive a plurality of pixel values; and implement processing of a particular pixel value by operating on a particular subset of the received pixel values, by: defining a set of one or more groups into which pixel values within the particular subset can be grouped; classifying each of the pixel values within the particular subset into one of the groups of the set of one or more groups based on the value of that pixel value; processing the particular pixel value using one or more of the pixel values of the particular subset in dependence on the classification of the pixel values of the particular subset into the one or more groups; and outputting the processed particular pixel value.