Image Processing Out-Focusing via Depth Region Segmentation
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Solution Overview
Problem
Digital single-lens reflex cameras struggle to provide an out-focus effect with a fixed focal length lens, limiting the ability to achieve a sharp focus in a predetermined depth region, while maintaining a compact camera size.
Innovation Solution
An image processing method that estimates regions based on depth values to adjust color values and apply blur strengths, calculating weights for boundaries and neighboring pixels to create an out-focused effect similar to a DSLR camera, using a color-depth camera to generate an out-focused color image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If a lens with unchangeable focal length is used in a color-depth camera, then the camera size is reduced, but the ability to provide an out-focus effect with sharp focus in a predetermined depth region is limited
Solution Approach 1:
The patent replaces the mechanical lens focusing system with an image processing system that uses depth information to selectively blur regions. Instead of mechanically adjusting lens focal length to achieve out-focus effects, the system processes captured images to simulate depth-of-field effects by identifying foreground and background regions based on depth maps and applying appropriate blur strengths, thereby achieving out-focus effects without changing the physical lens structure.
2Adaptability or versatility
If a lens with adjustable focal length is used to achieve out-focus effect, then the out-focus capability is improved, but the camera size increases
Solution Approach 1:
The patent creates a simulated out-focus effect by copying and processing depth information from the scene to generate a depth map, then using this depth map to guide selective blurring of image regions. Rather than using a complex adjustable lens system, the system captures the scene with a fixed lens and reproduces the out-focus effect through computational methods that copy depth relationships and apply corresponding blur operations.
3Measurement precision
If region segmentation based on depth values is performed, then the precision of out-focus control is improved, but the processing complexity increases
Solution Approach 1:
The patent segments the image into multiple depth-based regions (foreground, background, and region of interest) by comparing depth values against a reference focal length. This segmentation divides the complex task of out-focus processing into simpler sub-tasks: identifying regions to blur, determining blur strength for each region, and applying the blur selectively, thereby managing processing complexity through systematic division of the image space.
Solution Approach 2:
The patent applies different blur strengths to different spatial regions of the image based on their depth characteristics. Instead of uniformly processing the entire image, the system assigns local quality parameters (blur strength) to specific regions, allowing precise control over which areas are blurred and to what extent, thereby achieving high precision out-focus control with manageable processing requirements.
Data Source
AI summary
An apparatus and method for out-focusing a color image based on a depth image, the method including receiving an input of a depth region of interest (ROI) desired to be in focus for performing out-focusing in the depth image, and applying different blur models to pixels corresponding to the depth ROI, and pixels corresponding to a region, other than the depth ROI, in the color image, thereby performing out-focusing on the depth ROI.