Dual-Camera Depth Calculation with Synthetic Noise Reduction
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Solution Overview
Problem
Conventional dual-camera systems for image processing in mobile terminals face challenges in achieving accurate depth information and good imaging effects, especially in low-light environments, leading to poor blurring effects.
Innovation Solution
The system employs a method where a high-resolution camera is used as the main camera in bright conditions and a high-ISO camera in low-light conditions, with both cameras working together to acquire multiple frames, perform synthetic noise reduction, and calculate depth information using the triangulation ranging principle for improved blurring processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a dual-camera system is used to acquire two photos for background blurring processing, then depth information can be calculated and blurring effect can be achieved, but in dark environments the imaging effect becomes poor and depth information accuracy decreases
Solution Approach 1:
The patent segments the imaging task by using different cameras for different purposes: one camera (first camera) is dedicated to capturing the main image, while another camera (second camera) is dedicated to capturing depth information. This segmentation allows each camera to be optimized for its specific function, and crucially, allows the main image camera to use multiple frames for noise reduction without being constrained by the depth sensing requirement.
Solution Approach 2:
The patent performs preliminary noise reduction on multiple frames captured by the first camera before selecting a basic frame. By pre-processing multiple frames to reduce noise, the system ensures that the selected basic frame has high quality even in dark environments, before it is used for subsequent depth calculation and blurring processing.
2Reliability
If multiple frames are captured and processed for noise reduction, then imaging effect improves, but processing time and complexity increase
Solution Approach 1:
The patent performs noise reduction on multiple frames captured by the first camera before selecting a basic frame. By pre-processing multiple frames to reduce noise, the system ensures that the selected basic frame has high quality even in dark environments, before it is used for subsequent depth calculation and blurring processing.
Solution Approach 2:
The patent extracts only the necessary number of frames (n frames) from the multiple captured frames for noise reduction processing. Instead of processing all captured frames, the system selectively uses a subset of frames, which reduces processing time and computational complexity while still achieving effective noise reduction and improved imaging quality.
3Measurement precision
If conventional dual-camera systems are used in dark environments, then depth information can be obtained, but the accuracy of depth information and image quality deteriorate
Solution Approach 1:
The patent segments the imaging task by using different cameras for different purposes: one camera (first camera) is dedicated to capturing the main image, while another camera (second camera) is dedicated to capturing depth information. This segmentation allows each camera to be optimized for its specific function, and crucially, allows the main image camera to use multiple frames for noise reduction without being constrained by the depth sensing requirement.
Solution Approach 2:
The patent changes the operating parameters of the camera system by using different ISO values for the two cameras. The first camera uses a first ISO value optimized for image quality, while the second camera uses a second ISO value optimized for depth sensing. This parameter differentiation allows each camera to perform its specific function optimally, especially in dark environments where ISO settings critically affect performance.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the imaging effect and depth information accuracy, overcoming the limitations of poor image quality and low focusing speed in conventional dual-camera systems, especially in dark environments.
Implementation Method 1
calculate depth information of the main image according to the main image and the auxiliary image
Data Source
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AI summary
A method for image processing includes the following actions. After n frames of first images shot by a main camera are acquired and an auxiliary image shot by an auxiliary camera is acquired, synthetic noise reduction is performed on the n frames of first images to obtain a frame of main image. Depth information of the main image is further calculated according to the main image and the auxiliary image. Therefore, blurring processing is performed on the main image according to the depth information of the main image to obtain a required second image.