Defective Pixel Correction in Image Sensors
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Solution Overview
Problem
Existing image processing systems face reduced accuracy in interpolating pixel values for large clumps of defective pixels due to the reliance on distant normal pixels, leading to decreased interpolation accuracy near the center of the clump.
Innovation Solution
A digital camera system that classifies defective pixels into two types, corrects the first type by gain adjustment and smoothing, and interpolates the second type using corrected pixel values from neighboring pixels, maintaining edge sharpness and image structure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If interpolation is performed using pixel values from normal pixels positioned far outside the defective pixel clump, then the coverage area of correction is improved, but the interpolation accuracy near the center of the clump deteriorates
Solution Approach 1:
The patent segments the defective pixel clump into a center region and peripheral region. The center region (inner area) uses one interpolation method that prioritizes accuracy by using only peripheral normal pixels, while the peripheral region (outer area) uses another method that can utilize more distant normal pixels for broader coverage. This segmentation allows each region to be corrected with the most appropriate method for its specific needs.
Solution Approach 2:
The patent applies different correction strategies to different spatial locations within the defective pixel clump. For the center region where accuracy is critical, it uses a conservative interpolation approach with weighted averaging from peripheral pixels. For the peripheral region where coverage is more important, it can use more aggressive interpolation methods. This local differentiation resolves the contradiction by optimizing for accuracy where needed and coverage where possible.
2Stability of the object's composition
If gain correction is applied to all defective pixels, then the correction uniformity is improved, but the edge sharpness and image structure deteriorate
Solution Approach 1:
The patent applies different correction approaches to different regions: gain correction is applied uniformly to peripheral defective pixels where it maintains consistency, while the center defective pixels use interpolation from peripheral normal pixels to preserve edge sharpness and image structure. This local differentiation allows gain correction to be applied where it helps uniformity without compromising the critical edge regions.
Solution Approach 2:
The patent segments the defective pixel correction into two distinct approaches: one for peripheral pixels that can tolerate gain correction, and another for center pixels that require more sophisticated interpolation. This segmentation prevents the blanket application of gain correction from degrading edge sharpness while still achieving correction uniformity in regions where it is appropriate.
Data Source
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AI summary
An image processing device that corrects and interpolates pixel values of defective pixels present upon an image sensor, includes: a position information storage memory that stores a position of a defective pixel of a first type whose pixel value can be utilized after correction, and a position of a defective pixel of a second type whose pixel value is to be interpolated using pixel values of other pixels, distinguished from one another; a correction amount storage memory that stores a correction amount for the defective pixel of the first type; a correction unit that corrects the pixel value of the defective pixel of the first type according to the correction amount; and an interpolation unit that interpolates the pixel value of the defective pixel of the second type, using the pixel values of pixels including the defective pixel of the first type whose pixel value has been corrected by the correction unit.