Monitoring Camera Noise Reduction via Motion-Based Segmentation

Solution Overview

Problem

Existing monitoring camera systems struggle to prevent afterimages of focused subjects in captured images, especially in low-illuminate environments, while maintaining signal noise ratio (SNR) and recognition accuracy.

Innovation Solution

The system employs an imaging unit and a processor that differentiate between attention and non-attention portions in captured images, applying a lower intensity noise reduction processing on attention portions and a higher intensity on non-attention portions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If noise reduction processing is executed at high intensity to improve SNR in low-illuminate environments, then signal noise ratio is improved, but afterimage of moving body portion is increased

Engineering Contradiction:

Improvesignal noise ratioVSAvoidafterimage

Core Design Contradiction:

Measurement precisionVSObject-generated harmful factors

Solution Approach 1:

The image is divided into multiple regions based on motion detection results. Regions with motion (moving body portions) are segmented from regions without motion (still portions). Different noise reduction intensities are applied to different regions: high intensity for still portions to improve SNR, and low or zero intensity for moving portions to prevent afterimage generation.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The noise reduction processing intensity is made spatially variable rather than uniform. The processor dynamically adjusts the noise reduction intensity for each region based on its motion characteristics. This local quality approach allows optimal noise reduction for still regions while preserving motion fidelity in moving regions.

Inventive Principle:

Principle #3Local quality

2Object-generated harmful factors

If noise reduction processing is executed at low intensity to prevent afterimage, then afterimage is reduced, but signal noise ratio deteriorates

Engineering Contradiction:

ImproveafterimageVSAvoidsignal noise ratio

Core Design Contradiction:

Object-generated harmful factorsVSMeasurement precision

Solution Approach 1:

The image is divided into multiple regions based on motion detection results. Regions with motion (moving body portions) are segmented from regions without motion (still portions). Different noise reduction intensities are applied to different regions: high intensity for still portions to improve SNR, and low or zero intensity for moving portions to prevent afterimage generation.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The noise reduction processing intensity is made spatially variable rather than uniform. The processor dynamically adjusts the noise reduction intensity for each region based on its motion characteristics. This local quality approach allows optimal noise reduction for still regions while preserving motion fidelity in moving regions.

Inventive Principle:

Principle #3Local quality

3Device complexity

If uniform noise reduction processing is executed on entire image data, then processing is simple, but afterimage is generated for both attention and non-attention subjects

Engineering Contradiction:

Improveprocessing complexityVSAvoidafterimage

Core Design Contradiction:

Device complexityVSObject-generated harmful factors

Solution Approach 1:

The image is divided into multiple regions based on motion detection results. Regions with motion (moving body portions) are segmented from regions without motion (still portions). Different noise reduction intensities are applied to different regions: high intensity for still portions to improve SNR, and low or zero intensity for moving portions to prevent afterimage generation.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The noise reduction processing is made dynamic and adaptive rather than static and uniform. The processor continuously analyzes motion in the image and adjusts noise reduction parameters in real-time based on detected motion patterns. This dynamic approach automatically adapts to different scene conditions without requiring manual intervention.

Inventive Principle:

Principle #15Dynamics

Data Source

PatentUS12229923B2Monitoring camera and image quality improving method

Publication Date: 2025.02.18 PANASONIC I PRO SENSING SOLUTIONS CO LTD

AI summary

A monitoring camera includes an imaging unit configured to capture an image of an imaging area, and a processor configured to determine a first intensity and a second intensity to be different from each other. The first intensity indicates an intensity of a noise reduction processing executed on an attention portion in the captured image of the imaging area, and the second intensity indicates an intensity of a noise reduction processing executed on a non-attention portion in the captured image. The first intensity is lower than the second intensity. The processor is configured to execute the noise reduction processing on the attention portion based on the determined first intensity, to execute the noise reduction processing on the non-attention portion based on the determined second intensity, and to output an image after the noise reduction processing.