Weighted Image Averaging for Moving Object Noise Reduction
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Solution Overview
Problem
Existing electronic apparatuses struggle to effectively reduce noise in images captured from moving objects, as conventional methods of averaging multiple images can result in multiple compositing of moving subjects, leading to reduced image quality and amplified residual noise.
Innovation Solution
An electronic apparatus with an average image calculator and image quality processor that calculates a weighted average image using differences between images to avoid compositing moving objects, applying varying intensities of image processing based on weight maps to reduce noise and enhance image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are averaged to reduce noise, then noise reduction is improved, but multiple compositing of moving objects occurs causing image quality degradation
Solution Approach 1:
The patent segments the image processing into distinct functional modules: a moving object detector that identifies moving objects in each image, and an image combiner that selectively combines images while excluding moving objects. This segmentation allows the system to apply different processing strategies to different parts of the image data, reducing noise in stationary areas while preserving moving objects without compositing artifacts.
Solution Approach 2:
The patent applies local quality by treating stationary and moving regions differently within the same image sequence. Stationary regions undergo averaging to reduce noise, while moving object regions are handled separately to avoid multiple compositing. This localized differential processing resolves the contradiction by optimizing each region according to its characteristics.
2Measurement precision
If conventional image averaging is applied to all images, then noise is reduced, but residual noise is amplified in moving object regions
Solution Approach 1:
The patent extracts moving objects from the image sequence using a moving object detector before the averaging process. By taking out moving objects and processing them separately, the system avoids the amplification of residual noise that would occur if they were included in the conventional averaging process, while still achieving noise reduction in the stationary background regions.
3Measurement precision
If multiple images are captured to reduce noise, then noise reduction capability is improved, but processing complexity increases
Solution Approach 1:
The patent performs preliminary detection of moving objects in each captured image before the combining process. This preliminary action allows the system to prepare the image data in advance, marking or separating moving object regions so that the subsequent combining operation can efficiently process the images without complex real-time calculations, thereby managing processing complexity while maintaining noise reduction capability.
Data Source
AI summary
According to one embodiment, an electronic apparatus includes a calculator and a processor. The calculator calculates a weighted average image between a first image, a second image and a third image, by using a weight based on a difference between the first image and the second image and a difference between the first image and the third image. The processor applies, based on the weight, an image quality process of a first intensity to a first position in the weighted average image, applies an image quality process of a second intensity weaker than the first intensity to a second position in the weighted average image and to applies an image quality process of a third intensity weaker than the second intensity to a third position in the weighted average image.