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APPLICATIONS

Optical Solutions for High-Resolution Imaging Systems

Mosaic Optoelectronics develops specialized optical components for imaging systems where sensor sampling, polarization, reflections, birefringence, wavelength, and system geometry influence image quality or measurement.

APPLICATION AREAS

Start With the Optical Problem, Not the Catalog Part

The useful optical solution depends on what the imaging system is trying to resolve or measure, the sensor and lens architecture, illumination, wavelength, polarization, target geometry, and the artifacts that need to be controlled.

Machine Vision

High-resolution industrial imaging where sensor sampling, repeating structures, feature localization, and optical artifacts affect reliable inspection.

Electronics Inspection

Imaging of traces, pads, conductors, component arrays, solder features, grids, and other dense patterned structures.

Scientific & Metrology Imaging

Measurement and instrumentation systems where false image structure or optical behavior can influence quantitative results.

Specialized Imaging

Defense, aerospace, research, and custom sensing systems developed around unusual optical, mechanical, polarization, or spectral requirements.

MODERN SENSOR SYSTEMS

Small Pixels Change the Sampling Problem

Modern machine-vision sensors continue moving toward smaller pixels and higher sampling density. This allows finer detail to be captured, but it does not make the optical sampling problem disappear.

If the lens and scene deliver meaningful spatial detail near or above the sensor's sampling limit, aliasing can still occur. The relevant question is therefore not simply pixel size, but how the complete optical system interacts with the sensor sampling grid.

Lens MTF, magnification, aperture, wavelength, object structure, focus, and sensor pixel pitch all contribute to the spatial information present at the image plane.

Small-pixel sensor sampling and Nyquist comparison
Smaller pixels increase sampling capability, but they do not remove the sampling limit or the possibility of aliasing.

MACHINE VISION

Optical Control Before the Image Reaches the Algorithm

Machine-vision systems depend on consistent optical information before software begins interpreting the image.

Fine repeating structures can interact with the sensor sampling grid, reflective surfaces can reduce useful contrast, and polarization can change the visibility of important features.

Optical anti-aliasing, polarization control, and application-specific optical components can address these effects upstream of image processing.

In systems using small pixels and high-performance lenses, pre-sensor optical conditioning can be especially useful when the goal is to preserve reliable in-band detail while reducing false high-frequency structure.

COMMON OPTICAL CHALLENGES

  • Aliasing and moiré
  • Repeating or high-frequency patterns
  • Fine edge localization
  • Specular reflections
  • Surface glare
  • Low feature contrast
  • Limited optical-path space
  • Camera-specific integration requirements

AREA-SCAN & LINE-SCAN IMAGING

Sampling Behavior Depends on the Camera Architecture

The way spatial information is sampled differs between an area-scan array and a line-scan system that constructs the second image dimension through motion.

Area-scan and line-scan cameras can encounter different spatial sampling problems even when imaging similar targets.

Area-scan systems sample in two sensor dimensions simultaneously, while line-scan systems build the second image dimension through motion. Feature orientation, scan direction, pixel pitch, magnification, and target periodicity can therefore influence where aliasing becomes most significant.

Application-specific optical conditioning can be developed around the actual sampling geometry rather than assuming one universal filter response.

Area-scan and line-scan sensor sampling comparison
Area-scan and line-scan systems construct images differently, so sampling geometry, feature orientation, and motion can affect the resulting spatial response.

ELECTRONICS INSPECTION

Imaging Fine Structure on Complex Reflective Surfaces

Electronics inspection combines very small features with repeating patterns, mixed materials, reflective conductors, solder, coatings, and complex illumination.

Circuit traces, pad arrays, grids, component leads, and fine repetitive structures can generate strong high-spatial-frequency image content. At the same time, metallic and coated surfaces can create glare or polarization-dependent contrast.

The appropriate optical approach may involve anti-aliasing, polarization control, carefully selected crystal optics, or an integrated combination of several optical functions.

POSSIBLE OPTICAL APPROACHES

  • Optical anti-aliasing before sensor sampling
  • Structured spatial redistribution of image information
  • Polarization-based glare reduction
  • Control of reflected illumination
  • Custom optical stacks
  • Application-specific component geometry
  • Integration with inspection-camera optics

FINE PATTERNED STRUCTURES

Where Spatial Sampling Becomes Visible

Repeating features are especially useful for understanding why aliasing can become objectionable in industrial inspection.

When the projected spacing or orientation of a repeated pattern approaches the sensor sampling grid, small changes in alignment can create apparent structures, fringes, or periodic variation that do not represent the object itself.

Optical conditioning ahead of the sensor can reduce the energy in those problematic sampling relationships before they become digital artifacts.

Future Real Electronics-Inspection Image

High-magnification PCB, semiconductor, calibration grid, or dense conductor pattern showing repetitive structure where sensor sampling is immediately relevant.

SCIENTIFIC & METROLOGY IMAGING

False Image Structure Can Become Measurement Error

In quantitative imaging, a visually acceptable artifact can still affect measurement, feature localization, or interpretation.

Aliasing can create apparent spatial information that was not present in the original optical image. Depending on the measurement algorithm, that false structure can influence edge position, centroid estimation, periodicity measurements, or subpixel feature localization.

For these systems, optical filtering can be designed around the spatial information the measurement actually needs rather than around subjective image appearance alone.

RELEVANT CONSIDERATIONS

  • Pixel pitch and sensor geometry
  • Required measurement bandwidth
  • Lens MTF
  • Magnification
  • Operating wavelength
  • Polarization state
  • Feature orientation
  • Subpixel measurement requirements

PRE-SENSOR OPTICAL CONDITIONING

Structuring Image-Forming Light Before Sampling

Some imaging problems are best addressed before the light reaches the discrete sensor grid.

Birefringent optical elements can create controlled spatial displacement of image information. Multiple elements can be arranged to build an engineered point-spread pattern with selected displacement directions and separations.

This approach treats anti-aliasing as controlled spatial conditioning rather than generic blur. The design goal is to redistribute problematic high-frequency information while retaining as much useful image content as practical.

Structured optical conditioning before sensor sampling
Controlled optical redistribution can shape image information before the sensor converts it into discrete samples.

POLARIZATION & REFLECTION CONTROL

Sampling Is Only One Part of Image Quality

Many inspection problems combine sampling effects with polarization-dependent reflections and contrast.

Specular surfaces, transparent layers, coatings, metals, plastics, and anisotropic materials can all interact with polarization differently. Managing the polarization state can therefore reveal features, suppress glare, or stabilize image contrast.

In some systems, anti-aliasing and polarization control may be incorporated into the same multi-element optical assembly.

Polarization control reducing glare in reflective imaging
Conceptual illustration showing how polarization control can reduce specular glare and improve visibility of reflective features.

DEFENSE & AEROSPACE

Application-Specific Optics for Specialized Imaging and Sensing

Specialized imaging systems can involve unusual combinations of wavelength, packaging, environmental constraints, optical geometry, polarization, and sensing requirements.

In these applications, optical components are best evaluated against the actual system requirement rather than assumed from a standard configuration.

Mosaic Optoelectronics can evaluate specialized optical components and assemblies where crystal orientation, polarization, anti-aliasing, geometry, or integration are relevant to the imaging problem.

SYSTEM-DRIVEN REQUIREMENTS

  • Specialized imaging and sensing
  • Constrained optical packaging
  • Application-specific wavelength requirements
  • Polarization-sensitive optical behavior
  • Custom component geometry
  • Multi-element optical assemblies
  • Precision manufacturing and verification

COMMON OPTICAL PROBLEMS

The Same Optical Effect Can Appear in Very Different Industries

Rather than treating each market as a separate technology area, Mosaic focuses on the optical behavior that needs to be controlled inside the imaging system.

Aliasing

Fine image detail interacts with discrete sensor sampling and creates false spatial information.

Reflections

Surface glare or specular reflection obscures useful information or reduces feature contrast.

Polarization

Polarization state affects transmitted, reflected, or detected optical information.

Integration

Optical function must fit within a specific mechanical, geometric, sensor-level, or wavelength architecture.

QUANTITATIVE IMAGING

Machine Vision and Metrology

For measurement systems, false high-frequency image structure can perturb feature localization and subpixel measurement. Optical conditioning can therefore be optimized around the in-band spatial information the measurement actually needs.

SUBJECTIVE IMAGING

Cinema, Broadcast, and Photography

For visual imaging, the design goal may instead emphasize strong moiré and alias suppression while minimizing unnecessary loss of perceived sharpness.

APPLICATION DEVELOPMENT

Start With the Image or Optical Problem

You do not necessarily need to know which optical component is required before beginning a discussion.

Example images, sensor information, photographs of the system, existing optical components, drawings, wavelengths, or a description of the imaging problem can provide enough information to begin evaluating the optical approach.

From there, the issue can be considered in terms of sampling, lens MTF, polarization, materials, wavelength, geometry, optical integration, and manufacturability.

USEFUL APPLICATION INFORMATION

  • What the system is trying to image or measure
  • Example images showing the problem
  • Sensor model and pixel pitch
  • Lens and available MTF information
  • Magnification and working distance
  • Illumination arrangement
  • Operating wavelength or spectral range
  • Polarization information, if relevant
  • Available optical and mechanical space
  • Prototype and expected quantity requirements

HAVE AN IMAGING PROBLEM?

Start With What the Camera Is Seeing

Share the application, sensor, lens, example artifacts, and optical constraints. We can help determine whether anti-aliasing, polarization, crystal optics, or a custom optical assembly may be appropriate.

Construction Zone  Please excuse temporary issues while we complete the new Mosaic Optoelectronics website.