Image Sensor Remosaicing With Integrated Bad Pixel Correction
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Solution Overview
Problem
Existing image sensors face challenges in reducing error occurrence and improving image processing efficiency, particularly in handling bad pixels and remosaicing processes.
Innovation Solution
The proposed image sensor includes a pixel array with multiple color pixel groups and an image signal processor that performs bad pixel correction and remosaicing. The processor generates corrected pixel signals by using signals from adjacent color pixel groups and remosaices the signals to rearrange them in a higher frequency pattern, improving image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bad pixel correction is performed using conventional methods, then error occurrence is reduced, but image processing efficiency deteriorates due to complex processing steps
Solution Approach 1:
The patent combines bad pixel correction and remosaicing into a single integrated processing step. Instead of performing correction first and then remosaicing separately, the method performs both operations simultaneously by calculating corrected values for multiple color channels in one process, reducing the number of processing steps while maintaining correction accuracy
Solution Approach 2:
The processing method performs multiple functions in a single operation: it identifies bad pixels, calculates correction values using neighboring pixels, performs remosaicing to reconstruct the image pattern, and outputs corrected image data all in one unified process, improving efficiency without sacrificing reliability
2Manufacturing precision
If remosaicing is performed to rearrange pixels in higher frequency pattern, then image quality is improved, but processing complexity increases
Solution Approach 1:
The method performs preliminary identification of bad pixels and selection of neighboring correction pixels before the actual correction and remosaicing operation. By pre-processing the pixel selection and organization, the subsequent correction and remosaicing steps become more efficient and less complex, as the data structure is already optimized for the final processing
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution effectively reduces error occurrence and enhances image processing efficiency by accurately correcting bad pixels and improving the frequency pattern of the pixel signals, resulting in improved image quality.
Implementation Method 1
Each of the pixels may include, for example, a photodiode. The photodiode may convert incident light into an electrical signal.
Data Source
AI summary
An image sensor includes a pixel array including first to third pixel groups, including first to third color pixels having first to third colors and outputting first to third pixel signal for the first to third colors, and an image signal processor receiving the first to third pixel signals, wherein the image signal processor, when the first pixel signal is a bad pixel signal, performs bad pixel correction on the first pixel signal based on the second pixel signal and the third pixel signal and generates a remosaiced pixel signal for the first through third colors by remosaicing the second and third pixel signals based on each other, and the corrected pixel signal and the remosaiced pixel signal represent information in which the first through third color pixels are rearranged in a second pattern having a higher frequency than a frequency of a first pattern.