Image Processing for Reality Capture - 2/2

Course Title:  Image Processing for  Reality Capture: A Masterclass  Next Cohort 2nd February 2025

Course Description:  This course provides a comprehensive guide to mastering image processing techniques in Adobe Lightroom, Capture one and Photoshop. with over 30 hours tailored explicitly to enhance various reality capture methods and workflows. Learn how to optimise your images for 3D model creation, improve accuracy, and achieve stunning visual results, whether you're using photogrammetry, LiDAR, SLAM, or Gaussian Splats

QUALITY  IN = QUALITY OUT

Target Audience:

• Reality capture enthusiasts: Anyone using cameras to create 3D models, regardless of the specific technology.
• Photographers: Those familiar with Lightroom who want to apply their skills to enhance reality capture workflows.
• Professionals: Surveyors, engineers, architects, and anyone using reality capture technologies for precise 3D modelling.

Prerequisites:

• Basic understanding of reality capture principles (photogrammetry, LiDAR, SLAM, etc.).
• Access to Adobe Lightroom Classic.

Course Outline: 28 hours total

Module 1:  Foundations & Workflow (2 Hours)

• Lightroom for Reality Capture: 
  • Why image quality is crucial for accurate and visually appealing 3D models across different technologies.
  • Essential Lightroom tools and panels (Library, Develop).
  • Importing, organising, and culling images for various reality capture projects.
• RAW Processing Fundamentals: 
  • Understanding RAW files and their advantages for reality capture.
  • Developing a strong foundation in Lightroom's core image adjustment tools.
  • Applying professional techniques for initial image optimisation.

Module 2:  Precision & Control (3 Hours)

• Lens Corrections & Perspective: 
  • Correcting lens distortion for accurate geometry in 3D models.
  • Mastering perspective correction techniques for improved image alignment.
  • Using Lightroom's Transform tools to refine image composition.
• Exposure & Tonal Mastery: 
  • Achieving perfect exposure and contrast for detailed 3D models.
  • Optimising dynamic range to capture a wide range of tones.
  • Recovering highlights and shadows for balanced lighting.
• Colour Management & Grading: 
  • Ensuring accurate and consistent colours across all images.
  • Applying advanced colour grading techniques for visually harmonious 3D models.
  • Creating a cohesive look and feel for your reality capture projects.

Module 3:  Enhancing Detail & Clarity ( 2 Hours)

• Noise Reduction for Reality Capture: 
  • Understanding the impact of noise on 3D model generation across different technologies.
  • Applying effective noise reduction techniques while preserving image detail.
  • Balancing noise reduction with sharpness for optimal results.
• Sharpening Techniques: 
  • Enhancing image sharpness for improved feature detection in reality capture software.
  • Mastering sharpening techniques to achieve crisp and clear images.
  • Avoiding over-sharpening and artefacts that can hinder 3D model creation.
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Module 4: Masking for Reality Capture  ( 3 Hours)

• Types of Masks and Their Applications: 
  • Graduated Filters:  Correcting for uneven lighting and backgrounds.
  • Radial Filters:  Highlighting specific areas of interest.
  • Brush Tool:  Precise masking for complex shapes and objects.
  • Range Masks:  Targeting specific tonal or colour ranges.
• Masking for Sky  and Background Replacement: 
  • Creating realistic skies for improved 3D model backgrounds.
  • Blending techniques for seamless integration.
• Masking for Object Isolation: 
  • Isolating objects from their backgrounds for cleaner 3D models.
  • Removing distracting elements or unwanted artefacts.
• Advanced Masking Techniques: 
  • Refining edges and transitions for natural-looking masks.
  • Using luminosity masks to target specific brightness ranges.
  • Masking for glazing effects on reflective surfaces.
  • Combining multiple masks for complex adjustments.
• Object Removal for Cleaning Point Clouds: 
  • Removing small objects (wires, graffiti) that interfere with point cloud data.
  • Eliminating larger objects (vehicles, people) for cleaner colourisation and mesh generation.
  • Techniques for filling in gaps and maintaining visual consistency.

Module 5: Field Capture Techniques (2 Hours)

• Understanding Light and its Challenges: 
  • The impact of direct sunlight, shadows, and reflections on reality capture.
  • Dealing with mixed lighting conditions and colour casts.
  • Strategies for consistent colourisation as light changes throughout the day.
• Exposure Bracketing and HDR: 
  • Capturing bracketed exposures to handle high-contrast scenes.
  • Creating HDR images in Lightroom for improved dynamic range.
• Depth of Field and Focus Stacking: 
  • Controlling depth of field for optimal sharpness and detail.
  • Using focus stacking techniques for capturing images with extended depth of field.
• White Balance and Colour Consistency: 
  • Setting an appropriate white balance for accurate colour representation.
  • Maintaining colour consistency across multiple images captured in varying lighting conditions.
• Capturing Challenging Subjects: 
  • Photographing reflective surfaces and transparent objects.
  • Dealing with difficult lighting situations (e.g., interiors, low light).
  • Capturing details in shadowed areas and north-facing facades.

Module 6:  Optimising for Photogrammetry Software( 2 Hours)

• Exporting for 3D Model Generation: 
  • Choosing the best file format and resolution for your reality capture software (including considerations for LiDAR, SLAM, and Gaussian Splats).
  • Optimising export settings for maximum image quality and efficiency.
  • Exporting with metadata for accurate georeferencing and scaling.
• Batch Processing & Pre-sets: 
  • Streamlining image processing with batch editing tools.
  • Creating custom pre-sets for consistent results across large image sets.
  • Saving time and effort by automating repetitive tasks.
• Troubleshooting & Refinement: 
  • Addressing common image issues that can affect various reality capture software.
  • Analysing and refining images for optimal processing and accurate 3D models.
  • Developing a critical eye for identifying and correcting potential problems.

Module 7:  Advanced Techniques & Integration ( 3 Hours)

• HDRi & Panorama for Reality Capture: 
  • Creating HDR iiimages for improved dynamic range in challenging lighting conditions.
  • Batch processing plugins
  • Stitching panoramas for wider coverage and complete 3D scene capture.
  • Expanding your creative possibilities with advanced image techniques.
  • Introduction to Image Based Lighting ( IBL)
• RAW Editing  Capture Workflow: 
  • Seamlessly integrating RAW editing workflows  into your reality capture workflow, regardless of the technology used.
  • Importing and managing processed images for efficient 3D model creation.
  • Optimising your workflow for speed and productivity.
  • Introduction to Texturing and PBR Material
  • Introduction to Rendering

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• Case Studies & Best Practices: 
  • Analysing real-world examples of image processing for various reality capture methods.
  • Sharing best practices and tips for achieving high-quality results.
  • Learning from successful reality capture projects and industry experts

Module 8:  Image Management with Lightroom  (6 Hours).

A  complete course on managing and finding your images for you and your clients, colleagues and customers.  

Six hours of productivity and efficiency tools

New Module 9 PointCloud Cleaning and Mesh repair (5 hours)

Using Cloud Compare Rhino for point cloud and mesh optimisation.

• Point Cloud Processing:
  • Noise reduction and outlier removal.
  • Downsampling and point cloud simplification.
• Mesh Creation and Editing:
  • Generating meshes from point clouds.
  • Basic mesh editing tools (selection, deletion, smoothing).
  • Filling small holes and gaps.
• Mesh Analysis:
  • Identifying problematic areas using visualisation tools (normals, curvature).
• MeshRepair
• Hole Filling Techniques:
  • Patching large holes using different algorithms.
  • Refining and blending repaired areas.
• Geometry Correction:
  • Fixing non-manifold edges and vertices.
  • Removing self-intersections.
  • Smoothing and refining mesh surfaces.
• Developing an Efficient Workflow: Combining CloudCompare and Rhino for optimal mesh repair.
• Tips and Tricks: Best practices for achieving high-quality results.
• Case Studies: Examining real-world examples of mesh repair.

Throughout the course:

Hands-on Exercises:  Practical exercises with sample images and datasets from different reality capture technologies.

• Individual Feedback:  Personalised guidance on image processing techniques.
• Before & After Comparisons:  Visual demonstrations of the impact of image processing on 3D models.
• Resource Library:  Downloadable resources, pre-sets, and cheat sheets.
• One-to-one support.  The fee includes three hours one- to- one support  via Zoom/|Teams