Depth Map Generation via Iterative Blur Difference Analysis
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Solution Overview
Problem
Current image processing systems for capturing and displaying three-dimensional images face challenges in accurately correlating displayed information with the real world, leading to decreased benefits and inefficiencies, particularly in consumer and industrial electronics.
Innovation Solution
An image processing system that receives two images with different apertures, calculates the blur difference for their red and green channels, forms a depth map based on these differences, and uses this depth map to create a display image for improved three-dimensional representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple lenses are used to capture stereoscopic images for three-dimensional display, then depth information can be obtained, but device complexity and cost increase
Solution Approach 1:
The patent segments the depth estimation process into multiple iterations, where each iteration refines the depth map by comparing images captured at different apertures. This allows accurate depth estimation to be achieved through procedural segmentation rather than hardware complexity
Solution Approach 2:
The patent changes the aperture parameter of the lens to capture multiple images of the same scene at different focal depths. By varying this single parameter, the system obtains multiple perspectives needed for depth estimation without adding multiple lenses or cameras
2Measurement precision
If aperture is changed to estimate depth, then depth map can be generated, but processing time increases due to multiple image captures
Solution Approach 1:
The patent performs preliminary actions by capturing multiple images at different apertures in advance, storing them for later processing. This allows the depth estimation to be performed on pre-captured data rather than requiring real-time sequential capture, reducing perceived processing time
Solution Approach 2:
The patent maintains continuity of useful action by using all captured images across multiple iterations of depth estimation. Each iteration reuses the previously captured images, ensuring that the capture process is not repeated and maximizing the utility of each captured frame
Data Source
AI summary
A system and method of operation of an image processing system includes: a receive images module for receiving a first image having a first aperture and a second image having a second aperture with the first image and the second image each having a red channel and a green channel; a calculate blur difference module for calculating a red iteration count of a blur difference for the red channel of the first image and the second image, and calculating a green iteration count of the blur difference for the green channel of the first image and the second image; a calculate depth map module for forming a depth map having an element depth based on the red iteration count and the green iteration count; and a calculate display image module for forming a display image based on the first image and the depth map for displaying on a display device.