APD Image Correction for Crosstalk and Miscount Defective Pixels
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Solution Overview
Problem
Existing methods for correcting defective pixels in photoelectric conversion apparatuses with avalanche photodiodes (APDs) fail to distinguish between different causes of defects, leading to potential deterioration of image quality.
Innovation Solution
A processing apparatus and method that employs different weighting coefficients for correcting defective pixels based on the specific causes of miscounting, using a crosstalk matrix to predict and correct light-emission crosstalk for one type of defect and counter circuit miscounting for another, thereby reducing image quality deterioration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the same correction method is applied to all defective pixels, then light-emission crosstalk can be corrected, but image quality deteriorates due to erroneous correction of defects caused by other factors
Solution Approach 1:
The patent segments defective pixels into two categories: those caused by light-emission crosstalk and those caused by other factors. By classifying defective pixels based on their causes, the system applies appropriate correction methods only to the relevant type, avoiding erroneous correction of defects caused by other factors and thus maintaining image quality.
Solution Approach 2:
The patent applies different correction strategies to different types of defective pixels based on their specific causes. For light-emission crosstalk defects, a correction method using crosstalk probability matrices is applied, while for other types of defects, different handling is used. This localized quality approach ensures that correction is tailored to the specific defect type, preventing image quality deterioration.
2Measurement precision
If correction is applied to all defective pixels, then miscounting can be reduced, but defects caused by other factors are incorrectly corrected leading to image quality deterioration
Solution Approach 1:
The patent segments the correction process into two distinct paths: one for light-emission crosstalk defects and another for other types of defects. This segmentation ensures that the correction method using crosstalk probability matrices is applied only where appropriate, thereby maintaining count accuracy for crosstalk defects while avoiding incorrect correction of other defect types that would degrade image quality.
Solution Approach 2:
The patent changes the correction parameters based on the type of defective pixel. For light-emission crosstalk defects, specific correction parameters derived from crosstalk probability matrices are used. For other defect types, different parameters or correction methods are applied. This parameter change strategy ensures accurate correction for each defect type without compromising overall image quality.
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
Effectively suppresses image quality deterioration by accurately correcting defective pixels caused by different factors, minimizing miscounting and cluster defects in the surrounding areas.
Implementation Method 1
a photoelectric conversion apparatus is known which counts the number of photons incident on an avalanche photodiode (APD) and outputs the count value from a pixel as a photoelectrically-converted digital signal
Implementation Method 2
a phenomenon called avalanche light emission occurs in a photoelectric conversion apparatus having an APD. When avalanche light emission occurs, secondary electrons that are generated are incident on adjacent pixels
Data Source
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AI summary
A processing apparatus for generating and correcting an image based on a count value output by a photoelectric conversion element that has an avalanche photodiode, converts light from a subject into an electrical signal, counts the electrical signal, and outputs the count value, the processing apparatus generates a first image based on the count value, and executes correction processing for correcting the first image, wherein the correction processing includes first correction processing for a first pixel including a pixel in a surrounding area of a first type of defective pixel in which miscounting occurs due to a first cause, and second correction processing different from the first correction processing for a second pixel including a pixel in a surrounding area of a second type of defective pixel in which miscounting occurs due to a second cause different from the first cause.