Image Signal Processor Directional Component Extraction for Defective Pixel Correction
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Solution Overview
Problem
Existing image signal processors face challenges in accurately correcting defective pixels, particularly when multiple directional components are involved, which affects the quality of color images produced by image sensing devices.
Innovation Solution
An image signal processor that includes a directional component extractor, an interpolation kernel determiner, and a pixel interpolator, which perform convolution operations to extract directional components and determine interpolation kernels, allowing for precise interpolation of target pixels based on these kernels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional interpolation methods are used for defective pixel correction, then the processing is simple and fast, but the accuracy of defective pixel correction is insufficient when multiple directional components are involved
Solution Approach 1:
The patent segments the interpolation process into multiple stages: extracting directional components from the target kernel, determining multiple interpolation kernels based on different directions, and selectively applying appropriate kernels. This segmentation allows the system to handle multiple directional components systematically, improving correction accuracy while maintaining manageable process complexity through structured decomposition
Solution Approach 2:
The patent implements dynamic selection of interpolation kernels based on the extracted directional components. Instead of using a fixed interpolation method, the system dynamically determines which interpolation kernel to apply by analyzing the directional characteristics of the target kernel. This dynamic approach enables adaptive correction that responds to the specific directional patterns in the image data, thereby improving accuracy without requiring a completely complex static structure
2Measurement precision
If multiple interpolation kernels are determined based on directional components, then the correction accuracy improves, but the computational complexity increases
Solution Approach 1:
The patent applies local quality by determining different interpolation kernels for different directional components within the target kernel. Each directional component receives a customized interpolation approach based on its specific characteristics, rather than applying a uniform interpolation method across all pixels. This localized treatment improves precision for each directional component while optimizing computational resources by avoiding unnecessary complex calculations for uniform regions
3Adaptability or versatility
If directional components are extracted using convolution operations, then the handling of multiple directional components improves, but the processing time increases
Solution Approach 1:
The patent performs preliminary extraction of directional components from the target kernel before the main interpolation process. By pre-identifying and separating the directional components, the system prepares the data structure in advance, allowing the subsequent interpolation stage to proceed more efficiently. This preliminary action enables versatile handling of multiple directions while reducing the computational burden during the actual interpolation phase
Data Source
AI summary
An image signal processor includes a directional component extractor configured to extract directional components of a target kernel by performing a convolution operation between the target kernel including a target pixel and each of a plurality of directional kernels, an interpolation kernel determiner configured to determine an interpolation kernel based on the directional components, and a pixel interpolator configured to interpolate the target pixel using data included in the interpolation kernel.