Image Processing Apparatus Viewpoint Transformation Correction
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Solution Overview
Problem
Existing image display systems for vehicles face challenges in producing high-precision viewpoint transformed images when three-dimensional objects are captured, due to image distortion caused by low spatial resolution distance sensors.
Innovation Solution
An image processing apparatus and method that acquire captured images with high spatial resolution and depth information with lower spatial resolution, extract three-dimensional object areas, calculate depth information, correct coordinate transformation data, and generate high-precision viewpoint transformed images using the corrected data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a distance sensor with low spatial resolution is used to generate viewpoint transformed images, then the device complexity is reduced and cost is lowered, but image distortion occurs in three-dimensional objects and manufacturing precision deteriorates
Solution Approach 1:
The patent changes the parameter of depth information resolution by acquiring depth data at lower resolution than the captured image, then uses image recognition to identify three-dimensional object areas and applies selective coordinate transformation correction only to those areas. This allows using lower-resolution depth sensors while maintaining image quality for three-dimensional objects through parameter optimization and selective processing.
2Loss of information
If distance information with low spatial resolution is used for coordinate transformation, then the loss of information is reduced in terms of data processing load, but the measurement precision of three-dimensional object positions deteriorates
Solution Approach 1:
The patent applies local quality by making different parts of the image processing have different characteristics. Specifically, it identifies three-dimensional object areas through image recognition and applies enhanced coordinate transformation correction only to those specific regions, while other areas use standard transformation. This localized approach maintains high measurement precision for three-dimensional objects without unnecessarily processing the entire image at high resolution.
3Manufacturing precision
If high spatial resolution distance sensors are used to reduce image distortion, then the manufacturing precision of viewpoint transformed images is improved, but the device complexity and cost increase
Solution Approach 1:
The patent segments the image processing into distinct functional parts: captured image acquisition, distance image acquisition, three-dimensional object area extraction through image recognition, depth information calculation, and selective coordinate transformation correction. By segmenting the processing workflow and applying correction only where needed (in three-dimensional object areas), the system achieves high image precision without requiring high-resolution distance sensors across the entire field of view.
Data Source
AI summary
An image processing apparatus includes: an image acquisition unit that acquires a captured image with a first spatial resolution; a distance acquisition unit that acquires a distance image which is depth information with a second spatial resolution that is a resolution lower than the first spatial resolution; an image recognition unit that extracts an area including a three-dimensional object area corresponding to a three-dimensional object in the captured image; a distance calculation unit that calculates depth information of the three-dimensional object area on the basis of the distance image; a correction unit that corrects coordinate transformation information for coordinate transformation of the captured image on the basis of the depth information of the three-dimensional object area calculated by the distance calculation unit; and a viewpoint transformed image generation unit that generates a viewpoint transformed image obtained by the coordinate transformation of the captured image by using the coordinate transformation information corrected by the correction unit.