Volumetric Image Alignment and Colorization via Feature Detection

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Solution Overview

Problem

Manual image alignment between intensity images from laser scans and color photographs in video production is cumbersome and time-consuming.

Innovation Solution

A method and system for volumetric image alignment and colorization that captures intensity data with LIDAR scanners and color data with HDR cameras, using image feature detection to automatically align and colorize the images.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual image alignment is used to match points between color photograph and laser scan intensity image, then alignment accuracy can be achieved, but the process becomes cumbersome and time-consuming

Engineering Contradiction:

Improvealignment accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs automatic feature detection and matching between the color photograph and intensity image without requiring manual intervention. The computer automatically identifies corresponding features, calculates transformation parameters, and aligns the images, making the system self-sufficient in the alignment task.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The manual mechanical process of defining and matching corresponding points is replaced with an automated computer vision system that uses feature detection algorithms and image processing techniques to automatically align the images through digital computation.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If automated feature detection is used to align images, then processing time is reduced, but the complexity of the system increases

Engineering Contradiction:

Improveprocessing efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system integrates multiple functions into a single automated workflow: feature detection in both images, feature matching between images, transformation parameter calculation, and image alignment. This multi-functional approach streamlines the process while managing complexity through integration.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system automatically determines transformation parameters (translation, rotation, scaling) by analyzing feature correspondences between images. These parameters are calculated through mathematical optimization based on the detected features, allowing flexible adaptation to different image pairs without manual configuration.

Inventive Principle:

Principle #35Parameter changes

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Automates the image alignment and colorization process, significantly reducing processing time and improving efficiency in video production environments.

Implementation Method 1

capturing intensity data using at least one scanner, wherein the at least one scanner includes at least one LIDAR scanner

Methodology Applied

Scientific EffectLIDAR: LIDAR

Data Source

PatentUS12309500B2Trans-spectral feature detection for volumetric image alignment and colorization

Publication Date: 2025.05.20 SONY GROUP CORP

AI summary

Aligning and coloring a volumetric image, including: capturing intensity data using at least one scanner; generating an intensity image using the intensity data, wherein the intensity image includes at least one feature in a scene, the at least one feature including a sample feature; capturing image data using at least one camera, wherein the image data includes color information; generating a camera image using the image data, wherein the camera image includes the sample feature; matching the sample feature in the intensity image with the sample feature in the camera image to align the intensity image and the camera image; and generating a color image by applying the color information to the aligned intensity image.