Image Processing Device Correcting Fine Fixed Pattern Noise

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Solution Overview

Problem

Existing image processing devices struggle to efficiently detect and correct fine fixed pattern noise (FPN), which leads to image quality deterioration.

Innovation Solution

The implementation of an image processing device and system that utilizes Fast Fourier Transform (FFT) to detect FPN information, including period, start point, and LSB slope, and corrects FPN based on this information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If conventional FPN detection methods are used, then coarse FPN can be detected, but fine FPN cannot be efficiently detected

Engineering Contradiction:

ImproveFPN detection precisionVSAvoidFine FPN detection difficulty

Core Design Contradiction:

Measurement precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The image data is segmented into multiple image groups based on illuminance conditions, and further processed into average images. This segmentation allows the FPN detection to be performed on aggregated data that enhances the visibility of fine FPN patterns while reducing random noise interference.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent applies FFT analysis to average images formed by grouping multiple images under similar illuminance conditions. By performing the analysis on averaged data rather than individual images, the method achieves excessive action in terms of data aggregation, which enhances the detection capability for fine FPN that would be imperceptible in single images.

Inventive Principle:

Principle #16Partial or excessive action

2Reliability

If FPN correction is not performed, then processing is simpler, but image quality deteriorates

Engineering Contradiction:

ImproveImage qualityVSAvoidProcessing complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The FPN information is detected and stored in advance through FFT analysis of average images. This preliminary detection allows the correction process to use pre-characterized FPN patterns, reducing the complexity of real-time correction operations while maintaining high image quality.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

Average images serve as an intermediary between raw image data and FPN correction. By first creating average images from multiple images grouped by illuminance conditions, the system creates a intermediate representation that captures FPN characteristics while filtering out random noise, simplifying the subsequent correction process.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If multiple image groups are processed individually, then comprehensive FPN detection is achieved, but processing time increases

Engineering Contradiction:

ImproveFPN detection accuracyVSAvoidProcessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

Multiple images under similar illuminance conditions are merged into average images before FPN detection. This combining operation allows the system to process grouped data rather than individual images, reducing the total number of FFT operations needed while maintaining comprehensive FPN detection across different illuminance conditions.

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS20250184618A1Image processing devices, image processing systems and operating methods thereof

Publication Date: 2025.06.05 SAMSUNG ELECTRONICS CO LTD

AI summary

Provided are an image processing device configured to correct fine fixed pattern noise (FPN), an image processing system, and an operating method thereof. Provided is an operating method of an image processing device, the method including receiving at least one image group including a plurality of images, detecting, from the at least one image group, fixed pattern noise (FPN) information using Fast Fourier Transform (FFT), and correcting FPN based on the FPN information.