Lens Shading Correction Using Edge Pixel Luminance Weights
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Solution Overview
Problem
Existing methods for correcting lens shading in images require large memory capacity as they calculate and store luminance weight values for all pixels, which is inefficient and impractical.
Innovation Solution
The method partitions a reference image into blocks, extracts luminance values of edge pixels, calculates luminance weight values for these pixels, and uses these values to correct the luminance of input images by multiplying them with the corresponding pixel values, reducing the need for storing weight values for all pixels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If luminance weight values are calculated and stored for all pixels to correct lens shading, then lens shading correction accuracy is improved, but memory capacity requirements increase significantly
Solution Approach 1:
The patent divides the image sensor pixels into multiple blocks and further segments each block into a center region and edge regions. By calculating luminance weight values only for edge pixels in each block rather than all pixels, the method achieves lens shading correction while significantly reducing memory capacity requirements. The center pixels' weight values are derived from adjacent edge pixels, maintaining correction accuracy without storing all pixel values.
2Reliability
If luminance weight values are calculated for all pixels, then correction completeness is improved, but processing complexity and time increase
Solution Approach 1:
The patent extracts and identifies edge pixels from each block by comparing luminance values of adjacent pixels. Only these extracted edge pixels have their luminance weight values calculated and stored. The center pixels within each block derive their weight values from the extracted edge pixels, reducing processing complexity while maintaining correction completeness across the entire image sensor.
3Measurement precision
If luminance weight values are stored for all pixels, then correction accuracy is improved, but memory usage increases
Solution Approach 1:
The patent applies different treatment to different regions within each block: edge pixels have their luminance weight values explicitly calculated and stored, while center pixels derive their weight values from adjacent edge pixels. This local differentiation allows the system to focus memory resources on critical edge regions while reducing overall memory usage, maintaining correction accuracy through the relationship between edge and center pixel weights.
Data Source
AI summary
There is provided an image sensor according to an aspect of the present invention that includes: a reference image luminance extractor partitioning a reference image into a plurality of reference image blocks and extracting luminance values of edge pixels at the edges of each of the plurality of reference image blocks to calculate a luminance weight value for each of the edge pixels; a luminance weight value calculator calculating a luminance weight value of each pixel of the corresponding reference image block on the basis of luminance weight values of edge pixels of the corresponding reference image block with respect to each of the plurality of reference image blocks; and a luminance corrector correcting the luminance of an input image by multiplying the luminance weight value for each pixel calculated by the luminance weight value calculator with respect to a luminance value of each pixel of the input image.