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Visible and Infrared Multispectral Fusion Development Services

Winge provides visible, NIR, SWIR, and thermal infrared multispectral fusion development covering camera modules, synchronization and calibration, cross-spectral registration, fusion algorithms, RK3588 and Jetson deployment, SDKs, engineering prototypes, and written acceptance.

Image/vision/photoelectric sensor development

Multispectral fusion system development workflow

01Device and optical solution design
02Interface, driver, and synchronization design
03Calibration, registration, and fusion algorithms
04SDK, engineering prototype, and acceptance
Multi-bandImaging combinations
Hardware + softwareSystem coordination
AcceptableWritten criteria
SUPPORTED SYSTEM FORMS

Supported product and system forms

The service applies to imaging enhancement, target perception, night vision, thermal-target analysis, and industrial inspection, with coordinated hardware and software development based on project conditions.

The wavelength combination, component selection, platform adaptation, and delivery scope are subject to feasibility validation and the project technical agreement.

Service Detail

Visible and infrared multispectral fusion development services

For existing-system upgrades and new-product development, Winge provides phased engineering from technical assessment, camera modules and hardware design to calibration, registration, fusion algorithms, edge deployment, and engineering prototype validation.

What are visible and infrared multispectral fusion development services?

Visible and infrared multispectral fusion development services combine software, hardware, and algorithm engineering for visible, near-infrared, short-wave infrared, or thermal infrared imaging chains. The scope may include sensor and optics selection, camera modules, drivers, synchronization and calibration, cross-spectral registration, fusion enhancement, target analysis, edge deployment, SDKs, engineering prototypes, and written acceptance. The wavelength combination, devices, platform, performance targets, and delivery scope are defined from the application scenario, existing equipment, available data, and written technical agreement.

Project engagement models

The engagement model is selected from the available equipment, data conditions, and target deliverables: algorithm and data feasibility validation, adaptation of an existing system, or complete device and system development.

01

Algorithm and data feasibility validation

Applicable situation
Suitable when representative samples or a data-collection path are available and the project must first verify registration, fusion, or application-algorithm feasibility.
Service scope
Data-quality review, calibration-condition assessment, algorithm prototype, result analysis, and preliminary target-platform assessment.
Main deliverables
Algorithm prototype, assessment record, technical limitation list, and recommendations for subsequent development.
02

Existing-system adaptation

Applicable situation
Suitable when cameras, modules, or computing platforms already exist and interface, synchronization, calibration, algorithms, or deployment capabilities must be added.
Service scope
Interface and driver adaptation, timing synchronization, calibration tools, fusion algorithms, compute-platform adaptation, and system integration.
Main deliverables
Adaptation software, SDK, integration results, configuration information, and validation records.
03

Complete device and system development

Applicable situation
Suitable when the project requires coordinated development from imaging devices, hardware, and mechanical design through algorithms, software, engineering prototypes, and acceptance.
Service scope
System definition, component selection, hardware and mechanical design, low-level software, algorithms, edge deployment, and prototype validation.
Main deliverables
Design information, software and algorithms, SDK, engineering prototype, test records, and acceptance documentation.

Applications and technical value

In low light, backlight, smoke, occlusion, temperature variation, or complex backgrounds, a single imaging modality may not simultaneously support texture observation, thermal-target analysis, and intelligent recognition. A multispectral system combines visible-light texture with infrared radiation or reflection information to provide a unified imaging and data chain for human observation, device control, and algorithmic decisions.

Typical application directions: night or low-light imaging, thermal-target analysis, cross-spectral target tracking, industrial inspection, robot vision in complex environments, and upgrades of dual-spectrum devices.

Main development scope

01

Multispectral system definition

Define operating wavelengths, field of view, distance, illumination, temperature range, synchronization method, and environmental constraints.

02

Camera modules and hardware

Evaluate sensors, lenses, filters, illumination, interfaces, power, thermal design, and mechanical space.

03

Drivers and imaging pipeline

Adapt MIPI CSI-2, USB, GigE, GMSL, exposure control, ISP, encoding, and video streams.

04

Synchronization, calibration, and correction

Establish a common time base, intrinsic and extrinsic parameters, distortion models, coordinate systems, and temperature-drift correction procedures.

05

Cross-spectral registration and fusion

Develop registration, parallax compensation, fusion enhancement, salient-target preservation, and artifact suppression.

06

Multispectral intelligent analysis

Develop detection, tracking, segmentation, anomaly recognition, low-light enhancement, or thermal-target analysis for the target scenario.

07

Edge deployment and SDK

Adapt RK3588, Jetson, x86, or FPGA-assisted platforms and provide interfaces and examples.

08

Prototype and engineering validation

Complete an integrated prototype, test fixtures, scenario validation, issue closure, and milestone acceptance.

Supported spectra and imaging chains

On mobile devices, swipe horizontally to view the complete table.

Input typeTypical useEngineering focus
RGBTexture, color, detail, and conventional vision algorithmsResolution, low-light performance, dynamic range, ISP, and lens
NIRNight illumination, low-light recognition, and material-contrast enhancementIllumination wavelength, filtering, reflectance, and eye safety
SWIRAssessment of selected materials, imaging in haze, and industrial inspectionComponent availability, lens, cost, and data availability
MWIR / LWIRThermal-target imaging, temperature-difference analysis, and day/night environmental sensingCore performance, NUC, lens, temperature drift, and temperature-measurement boundaries

Multispectral fusion system pipeline

System development normally includes multi-channel acquisition, time synchronization, geometric calibration, cross-spectral registration, fusion enhancement, target analysis, and edge output. Each stage affects final imaging and downstream algorithm results.

  1. 01Multi-channel acquisition
  2. 02Time synchronization
  3. 03Geometric calibration
  4. 04Cross-spectral registration
  5. 05Fusion enhancement
  6. 06Target analysis
  7. 07Edge output
RK3588Assessment of NPU, GPU, and RGA coordination at the edge
JetsonCUDA, TensorRT, and video-pipeline integration
x86Deployment on desktops, servers, and industrial computers
FPGAAssessment of assisted acquisition, synchronization, and preprocessing

Project deliverables

Hardware and modules

Schematics, PCB or interface information, BOM recommendations, mechanical and thermal constraints, and engineering prototypes.

Low-level software

Drivers, firmware, acquisition and synchronization programs, ISP or encoding configuration, and device diagnostic tools.

Algorithm capabilities

Calibration, registration, fusion, enhancement, and scenario algorithms, with models and parameters managed by project version.

Integration interfaces

SDK, API, example projects, data formats, deployment scripts, and third-party system integration instructions.

Validation documentation

Calibration records, test data, issue lists, performance reports, acceptance records, and maintenance recommendations.

Testing and acceptance

Acceptance criteria must identify the applicable devices, lenses, distance, illumination, temperature, test data, software version, and runtime platform, with the test methods and pass conditions defined in the written technical agreement.

SynchronizationMulti-channel image time offset, jitter, dropped frames, and trigger stability
RegistrationRegistration residual, edge misalignment, and parallax compensation under agreed distances and scenes
FusionTarget visibility, detail preservation, noise, halo, ghosting, and switching stability
DeploymentEnd-to-end latency, frame rate, compute utilization, memory, power, temperature rise, and continuous operation
Application algorithmsDetection, tracking, or segmentation metrics evaluated on the written sample set and test conditions

Technical and delivery boundaries

Thermal imaging does not automatically provide radiometric temperature measurement. Frame rate, algorithm metrics, power, environmental rating, temperature-measurement capability, and production status must be confirmed after validation on the actual devices, data, and target platform. Third-party components, software, licenses, data, and customer equipment remain subject to their actual availability and terms.

Frequently asked questions

Can existing cameras and hardware platforms be retained?

The existing sensors, lenses, output formats, trigger methods, driver support, and compute headroom must be assessed. If interfaces, time synchronization, or field-of-view matching do not meet the project target, an adapter board, synchronization unit, or revised camera module may be required.

Which infrared bands are supported?

A project may involve NIR, SWIR, and mid-wave or long-wave thermal infrared. The devices, lenses, calibration method, and cost range depend on the target distance, environmental conditions, temperature range, and component availability.

Can the project cover only the fusion algorithm?

Yes. The project must provide usable dual-spectrum or multispectral data, calibration information, and target-platform details. Work can then proceed in phases covering data assessment, algorithm prototype, engineering implementation, platform deployment, and acceptance.

Is deployment on RK3588 or Jetson available?

RK3588, Jetson, x86, or FPGA-assisted platforms can be assessed for the project. Feasibility validation examines operator support, numerical precision conversion, memory bandwidth, video pipelines, and end-to-end latency before the deployment scope is confirmed.

How should acceptance criteria for a multispectral fusion system be defined?

The criteria must define cameras, lenses, distance, illumination, temperature, target type, test data, software version, and runtime platform, and separately specify synchronization, registration, fusion artifacts, latency, and downstream task metrics.

Is thermal imaging equivalent to temperature measurement?

No. Temperature-measurement metrics are appropriate only with a radiometric core, a calibration procedure, emissivity settings, and environmental compensation. A conventional thermal-imaging project evaluates imaging and target-analysis capabilities only.

Delivery Process

Project implementation and delivery process

Phased assessment, development, integration, and testing are used to confirm the technical solution, delivery scope, and written acceptance conditions.

01Requirements and scenario analysis

Confirm the application scenario, operating wavelengths, target distance, environmental conditions, runtime platform, and acceptance objectives.

02Feasibility validation

Use representative devices and data to validate imaging, synchronization, registration, fusion, and compute conditions.

03Technical solution confirmation

Confirm components, interfaces, algorithm flow, deliverables, test methods, and change boundaries.

04Development and system integration

Complete hardware, drivers, calibration, algorithms, edge deployment, and system integration.

05Scenario testing and acceptance

Test imaging pipelines, algorithm metrics, stability, and environmental adaptability under written conditions.

06Deployment and documentation delivery

Deliver the agreed source code, SDK, engineering prototypes, technical documents, test records, and maintenance recommendations.

Multispectral fusion project assessment

Submit the target scenario, existing equipment, target platform, and acceptance requirements so the technical route, development scope, and implementation conditions can be confirmed.

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