Image Processing Apparatus Depth Map Correction via Misalignment Detection
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Solution Overview
Problem
Existing image processing techniques for estimating focusing distance from photographed images often result in image quality deterioration due to errors in depth map generation, particularly in areas with minimal blur, leading to incorrect blurring effects where the main object is blurred unnecessarily and the background is not blurred enough.
Innovation Solution
An image processing apparatus and method that detects misalignment among images, acquires distance information, and creates reliability information based on detected misalignment to correct the depth map, thereby reducing errors in focusing distance estimation and improving image quality by adjusting the blurring process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If passive methods (DFD or stereo) are used to create a depth map from photographed images, then no special apparatus is required and the method is simple, but accurate distance estimation becomes difficult in certain photographed scenes, leading to incorrect depth maps
Solution Approach 1:
The patent introduces an active illumination source (projector) as an intermediary to project structured light patterns onto the object. This mediator enables accurate depth measurement by providing known reference patterns that can be reliably correlated between multiple views, solving the accuracy problem of passive methods while maintaining ease of implementation through a straightforward active ranging setup.
Solution Approach 2:
The patent changes the measurement approach from passive light analysis to active structured light projection. By projecting known light patterns with specific spatial parameters and analyzing their deformation, the system transforms an ill-posed passive estimation problem into a well-posed active measurement problem, achieving high accuracy in distance estimation.
2Productivity
If an incorrect depth map is used to generate an image with shallow depth of field, then processing can still be completed, but image quality deteriorates with incorrect blurring effects in main object areas and insufficient blurring in background areas
Solution Approach 1:
The patent implements a feedback mechanism where the system first performs initial depth estimation, identifies unreliable regions based on measurement confidence or consistency checks, and then applies targeted corrections or adjustments in those specific areas. This feedback loop ensures that the final depth map produces reliable blurring effects throughout the image while maintaining overall processing efficiency.
Solution Approach 2:
The patent applies different processing quality levels to different regions of the image based on local reliability assessments. High-priority accurate depth estimation is applied to critical regions (main objects), while lower-priority regions (background) use standard processing, optimizing the balance between overall image quality and processing efficiency.
Data Source
AI summary
An image processing apparatus that acquires a focusing distance from a plurality of images each having different degrees of blur, comprises a misalignment detection unit that detects misalignment among the plurality of images; a distance information acquisition unit that acquires, based on the plurality of images, distance information, which is information to indicate a focusing distance in an area of the images; and a reliability information acquisition unit that creates, based on the detected misalignment, reliability information, which is information to indicate reliability of the focusing distance acquired for each area, wherein the distance information acquisition unit changes the acquired distance information based on the reliability information.