Image Sensor Noise Filter for Diffractive Optical Element Interference
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The challenge is to enhance the optical precision of cameras, particularly with the increasing pixel count and addition of features like auto-focusing and optical-zoom, where existing technologies have not effectively addressed noise issues caused by diffractive optical elements in lens units.
Innovation Solution
Incorporating an image sensor with a noise filter that converts incident light into electrical image signals and removes noise using a diffractive optical element, along with an image processing unit to generate high-quality screen image data, and a lens unit that includes diffractive optical elements to improve optical precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If diffractive optical elements are applied to the lens unit, then optical precision is improved, but noise is generated in the electrical image signal
Solution Approach 1:
The patent applies a noise filter to the image sensor that specifically targets and removes noise generated by diffractive optical elements. The filter converts the harmful noise effect into a benefit by selectively eliminating only the diffractive noise while preserving the actual image signal, thereby maintaining the optical precision improvements from the DOE while eliminating its adverse effects
Solution Approach 2:
The noise filter acts as an intermediary component between the image sensor and the image processing unit. It mediates the electrical image signal by removing diffractive noise before the signal is processed further, allowing the system to benefit from both the DOE's optical precision enhancement and clean image signals
2Measurement precision
If pixel count is increased to more than 8 megapixels, then image quality is improved, but noise removal becomes more difficult
Solution Approach 1:
The noise filter is designed to operate locally on the electrical image signal at the pixel level. By applying noise removal processing to each pixel or small groups of pixels individually, the system can handle high megapixel counts without requiring complex global processing, thus maintaining image quality while managing noise removal complexity
Solution Approach 2:
The noise filter performs noise removal as a preliminary action before the image signal undergoes further processing. By removing diffractive noise early in the signal chain, the system simplifies subsequent processing steps and makes noise removal more manageable even with high pixel counts
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 solution effectively converts incident light into electrical image signals, removes noise, and enhances the optical precision of cameras, even when diffractive optical elements are used, resulting in improved image quality.
Implementation Method 1
the lens unit may include a diffractive optical element
Implementation Method 2
an image detecting unit for converting an incident light into an electrical image signal
Data Source
AI summary
Disclosed are a camera, an image sensor thereof, and a driving method thereof. An image sensor converts an incident light into an electrical image signal. The image sensor outputs the converted electrical image signal by removing noise from the electrical image signal. An image processing unit processes the output image signal to generate screen image data. The image sensor effectively removes noise, thereby improving the optical precision of the camera.