Under-Display Camera Deblurring for Diffraction Artifact Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The positioning of a digital camera underneath a display panel in under display camera (UDC) systems creates image quality issues due to noise and light diffraction artifacts, leading to low signal-to-noise ratios, significant light source diffraction artifacts, and low resolution, which reduces overall image quality.
Innovation Solution
Obtain multiple image frames with different diffraction patterns related through a transformation, generate deblurred images using multi-frame processing and point spread function inversion, and combine these images to exploit complementary image artifacts, improving image quality by merging aligned deblurred images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a digital camera is positioned underneath an OLED display panel to hide the camera from user view, then the display panel can occupy most or all of the user-facing surface area, but light diffraction caused by the periodic pattern of the display panel creates noise and reduces image quality
Solution Approach 1:
The patent applies the 'Blessing in disguise' principle by capturing images with intentional display panel diffraction patterns and then using computational methods to remove these patterns. The harmful diffraction artifacts are converted into a solvable computational problem, where the periodic nature of the artifacts provides information about the display panel structure that can be used to synthesize clean images through iterative image formation and refinement processes.
2Measurement precision
If multiple image frames with different diffraction patterns are obtained and processed to reduce diffraction effects, then image quality and signal-to-noise ratio improve, but processing complexity and computational requirements increase
Solution Approach 1:
The patent applies segmentation by dividing the image processing task into multiple stages: capturing multiple image frames with different diffraction patterns, separating the diffraction pattern removal process from the image formation process, and iteratively refining the result. This modular approach manages complexity by breaking down the overall processing into manageable segments that can be optimized independently.
Solution Approach 2:
The patent implements feedback through an iterative image formation and refinement process. The algorithm uses the difference between captured images with diffraction patterns and the desired clean images to generate correction terms, which are then fed back into the iterative process to progressively improve the image quality. This feedback mechanism automatically adapts to different diffraction patterns and scene conditions.
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
The technique enhances image quality by improving signal-to-noise ratios, reducing light source diffraction artifacts, and increasing resolution through the combination of deblurred images with complementary artifacts.
Implementation Method 1
a digital camera is positioned underneath a semi-transparent organic light-emitting diode (OLED) display panel
Implementation Method 2
light diffraction caused by the periodic pattern of OLED display panels
Data Source
AI summary
A method includes obtaining, using at least one under display camera, one or more first image frames associated with a first diffraction pattern and one or more second image frames associated with a second diffraction pattern. The first diffraction pattern and the second diffraction pattern are related through a transformation. The method also includes generating a first deblurred image using the one or more first image frames and a second deblurred image using the one or more second image frames. The method further includes combining the first and second deblurred images while exploiting complementary types of image artifacts created by the first and second diffraction patterns to generate an image of a scene.