Motion Sensor-Based Video Noise Reduction

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Solution Overview

Problem

CMOS image sensors in personal electronic devices introduce noise due to camera movement or low light conditions, leading to geometric distortion and artifacts in captured video, which existing noise reduction techniques fail to address effectively in real-time.

Innovation Solution

The use of motion sensor data, such as from accelerometers and gyrometers, to generate a perspective transformation matrix that corrects for camera motion, allowing for the reduction of noise by merging pixels between frames based on motion data and camera parameters, thereby overcoming real-time constraints of traditional noise processing methods.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Object-affected harmful factors

If traditional noise reduction techniques are used on captured video frames, then noise may be reduced, but real-time processing constraints are violated due to high computational costs

Engineering Contradiction:

Improvenoise in video framesVSAvoidreal-time processing capability

Core Design Contradiction:

Object-affected harmful factorsVSProductivity

Solution Approach 1:

The patent applies preliminary action by using motion sensor data to predict and compensate for geometric distortions before noise reduction processing. The distortion correction is performed upfront based on accelerometer and gyrometer readings, which simplifies subsequent noise reduction operations and enables real-time processing by avoiding computationally intensive post-processing steps.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent replaces traditional mechanical/image-based noise reduction approaches with a sensor-driven computational approach. Instead of relying solely on complex image processing algorithms, the system substitutes motion sensor data (accelerometer and gyrometer readings) to guide the noise reduction process, significantly reducing computational requirements while maintaining real-time performance.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Manufacturing precision

If motion sensor data is used to correct geometric distortion, then image quality improves, but device complexity increases due to additional sensors and processing

Engineering Contradiction:

Improvegeometric accuracy of captured imagesVSAvoidsystem complexity with motion sensors

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent applies universality by using motion sensor data for multiple purposes: it corrects geometric distortion in video frames, guides noise reduction processing, and provides temporal synchronization information. This multi-functional use of the same sensor data reduces the need for additional specialized components, thereby limiting the increase in device complexity while achieving improved geometric accuracy.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS8928765B2Noise reduction based on motion sensors

Publication Date: 2015.01.06 APPLE INC

AI summary

A method for reducing noise in a sequence of frames may include generating a transformed frame from an input frame according to a perspective transform of a transform matrix, wherein the transform matrix corrects for motion associated with input frame. A determination may be made to identify pixels in the transformed frame that have a difference with corresponding pixels in a neighboring frame below a threshold. An output frame may be generated by adjusting pixels in the transformed frame that are identified to have the difference with the corresponding pixels in the neighboring frame below the threshold.