Depth Map Histogram Analysis for Natural Blur Synthesis
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Solution Overview
Problem
Existing image processing techniques struggle to accurately create a blurred background while maintaining the sharpness of in-focus objects, especially in low-performance optical systems, and require specialized equipment or user-defined parameters, leading to unnatural images and operational difficulties.
Innovation Solution
An image processing apparatus that acquires a depth map to determine depth distances and uses this information to control blur amounts based on defocus deviations from the in-focus position, ensuring the in-focus object remains sharp and the background is blurred according to the photographer's intention, without requiring complex user input or specialized cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a depth map is used to determine blur amounts based on defocus deviations, then the in-focus object can be kept sharp and background can be blurred, but errors in depth map estimation cause unnatural blur effects where in-focus objects may be incorrectly blurred
Solution Approach 1:
The patent introduces a histogram of depth distances as an intermediary statistical representation to mediate between the noisy depth map data and the final blur application. By converting individual depth measurements into a distributed histogram and identifying the mode (most frequent depth), the system filters out noise and outliers, ensuring that the in-focus object's depth is accurately determined even when individual depth map values contain errors.
Solution Approach 2:
The patent creates a histogram copy of the depth distance distribution and operates on this statistical representation rather than directly on the original depth map values. This copying approach allows the system to analyze the distribution pattern, identify the dominant depth (mode), and determine blur amounts based on this robust statistical measure, thereby avoiding the impact of individual erroneous depth measurements.
2Measurement precision
If specialized three-dimensional measurement cameras are used to achieve high-quality blur effects, then accurate depth information can be obtained, but the device complexity and cost increase significantly
Solution Approach 1:
The patent replaces the need for complex mechanical three-dimensional measurement cameras with a computational approach using standard image sensors. By utilizing depth from defocus (DFD) algorithms that analyze focus variation across the image, the system extracts depth information from ordinary photographs, thereby substituting complex hardware with software-based optical processing.
Solution Approach 2:
The patent enables the standard camera system to perform depth measurement functions that would otherwise require specialized equipment. By using the camera's own optical characteristics (depth of field, focus mechanism) and processing the captured image data through DFD algorithms, the system makes the ordinary camera self-sufficient for obtaining depth information without external specialized devices.
3Manufacturing precision
If user-specified camera parameters and focal positions are required for blur processing, then precise control over blur effects can be achieved, but the ease of operation decreases
Solution Approach 1:
The patent enables the system to automatically determine the focal position and depth parameters by analyzing the depth map histogram and identifying the mode depth. This self-service approach eliminates the need for manual user input, allowing the camera to autonomously calculate the appropriate blur amounts for different regions based on the statistical distribution of depth distances in the captured image.
Solution Approach 2:
The patent implements a feedback mechanism where the depth map data is continuously analyzed to generate a histogram, which then feeds back into the determination of the mode depth and subsequent blur amount calculations. This closed-loop process automatically adjusts the blur parameters based on the actual depth distribution in the scene, ensuring accurate blur effects without requiring manual user specification.
Data Source
AI summary
An image processing apparatus has: a depth map acquiring unit configured to acquire a depth map that records information indicating a depth distance corresponding to each point on a photographed image; an in-focus position acquiring unit configured to acquire an in-focus position on the photographed image; a reference distance determining unit configured to acquire a depth distance corresponding to the in-focus position from the depth map and sets the acquired depth distance as a reference distance; and an image processing unit configured to perform image processing on the photographed image by using the depth map and the reference distance.