Adaptive Green Sub-pixel Compensation for Bayer Pattern Luminance Unbalance
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Solution Overview
Problem
Image sensing elements, such as CMOS image sensors, face issues with green unbalance due to differing interference levels from surrounding pixels in Bayer pattern arrays, leading to problems like latticed images, false colors, and blurry edges in image reconstruction.
Innovation Solution
An adaptive pixel compensation method that calculates average luminance values and absolute differences between green sub-pixels on different-type pixel rows, along with luminance gradient values, to determine if compensation is needed for green sub-pixels, thereby addressing luminance property differences and preserving image details.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If green sub-pixels are arranged in Bayer pattern with dominant proportion, then green color visual information detail discernment is improved, but green unbalance occurs due to different interference levels from surrounding pixels
Solution Approach 1:
The patent applies local quality by differentiating compensation processing for green sub-pixels based on their row type (first-type with red neighbors vs. second-type with blue neighbors). Different compensation values are calculated and applied to green sub-pixels in different locations, making the compensation adaptive to local luminance characteristics rather than applying a uniform correction across all green pixels.
Solution Approach 2:
The patent changes the luminance parameter of green sub-pixels by calculating compensation values based on the difference between average luminance of first-type and second-type pixel rows. The compensation value dynamically adjusts the luminance parameter of each green sub-pixel according to its specific row type and surrounding pixel characteristics, thereby correcting the green unbalance.
2Reliability
If pixel compensation is applied to correct green unbalance, then green sub-pixel luminance consistency is improved, but image blurring may occur due to excessive smoothing
Solution Approach 1:
The patent preserves image details by applying different compensation strategies to different regions. Green sub-pixels in first-type rows and second-type rows receive different compensation values calculated from their respective surrounding pixel statistics. This localized approach prevents uniform smoothing that would blur edges, while still correcting the systematic green unbalance in each region.
Solution Approach 2:
The compensation process is dynamic rather than static. The patent calculates compensation values based on actual luminance measurements from surrounding pixels in the image data, making the compensation adaptive to local image content. This dynamic adjustment allows the system to correct green unbalance while preserving genuine image details and edges.
Data Source
AI summary
An adaptive pixel compensation method for an image processing apparatus includes receiving an image array data, calculating an average of luminance values of a first plurality of green sub-pixels surrounding the green sub-pixel as a first average value, calculating an average of luminance values of a second plurality of green sub-pixels surrounding the green sub-pixel as a second average value, calculating an absolute luminance difference value of the first average value and the second average value, calculating an average luminance gradient value of the green sub-pixel and a third plurality of green sub-pixels surrounding the green sub-pixel, and determining whether to compensate the green sub-pixel according to a luminance value of the green sub-pixel, the absolute luminance difference value and the average luminance gradient value.