Imaging Apparatus Depth Map Generation via Deconvolution
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Solution Overview
Problem
Conventional methods for measuring distance using imaging apparatuses face challenges such as complex camera configurations, decreased light sensitivity, and high calculation costs, particularly in consumer-targeted cameras.
Innovation Solution
The solution involves generating an all-in-focus image without prior edge information, allowing for direct evaluation of blur amounts and distance estimation using deconvolution processing, which simplifies camera configuration, maintains light sensitivity, and reduces calculation costs by eliminating the need for repeated evaluation function calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a multi-focus camera with coding opening is used to simultaneously capture three images having different focal points, then distance estimation stability and precision are improved, but camera configuration complexity increases
Solution Approach 1:
The patent divides the image capturing process into multiple sequential captures at different focal points rather than using a complex multi-focus camera. The imaging apparatus captures a first image at a first focal point and a second image at a second focal point separately, then processes these segmented images to estimate depth. This segmentation approach achieves the same depth estimation functionality with simpler hardware.
Solution Approach 2:
The patent performs preliminary actions by capturing images at extreme focal points (near end and far end) before performing the actual depth estimation. These preliminary captures establish the blur characteristics needed for deconvolution processing, which then enables accurate distance measurement without requiring complex simultaneous multi-focus capture hardware.
2Measurement precision
If a coding opening with narrowed aperture is used to create marked blur difference, then distance measurement capability is improved, but light amount decreases
Solution Approach 1:
The patent extracts the blur information needed for depth estimation from the image data itself through deconvolution processing, rather than relying on a coding opening to create artificial blur patterns. By removing the need for special aperture structures, the system maintains full light transmission capability while still achieving accurate blur-based distance measurement.
Solution Approach 2:
The patent replaces the mechanical aperture restriction (coding opening) with a computational approach. Instead of physically narrowing the aperture to create blur differences, the system uses digital image processing and deconvolution algorithms to extract and utilize blur information, substituting mechanical light control with computational analysis.
3Measurement precision
If repeated calculation with evaluation function is performed to estimate distance, then distance estimation accuracy is improved, but calculation cost increases
Solution Approach 1:
The patent employs self-service by using the captured images themselves as the basis for direct blur amount calculation through deconvolution. Rather than requiring complex iterative optimization with evaluation functions, the system directly processes the image data to extract blur characteristics, making the calculation more efficient and less computationally intensive while maintaining accuracy.
Data Source
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AI summary
The present invention provides an imaging apparatus which generates, based on a captured image, a depth map of an object with a high degree of precision. A sensor drive unit (12) that shifts an image sensor (11) in an optical axis direction, along with a sensor drive control unit (13), capture images A and C which are focused on a near end side and a far end side of the object, respectively, and an image B by sweeping the image sensor (11) from the near end side to the far end side, an all-in-focus image generation unit (15) generates an all-in-focus image D from the sweep image B, a blur amount calculation unit (16) calculates an amount of blur in each of the partial regions of the images A and B through deconvolution processing in an image of a region corresponding to the all-in-focus image D, and a depth map generation unit (17) generates a distance between the imaging apparatus and the object in each of the image regions, in other words, a depth map, from an amount of blur in regions corresponding to the near end image A and the far end image C and from an optical coefficient value of the imaging apparatus including a focal length of a lens.