Distance Image Noise Reduction via Segmented Pixel Filtering
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Solution Overview
Problem
Conventional noise reduction techniques for distance images, such as median filtering, often amplify noise and increase defective pixels, making it necessary to develop a more effective method for noise reduction in distance images acquired by image capture devices like ToF cameras.
Innovation Solution
An image processing apparatus with an input interface, image divider, noise filter, and image combiner that divides distance images into pixel groups based on distance intervals and applies distinct filter parameters to each group to reduce noise, while combining processed groups to generate a cleaner distance image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If conventional noise reduction techniques such as median filtering are applied to distance images, then noise reduction is attempted, but noise is amplified and defective pixels increase
Solution Approach 1:
The patent divides the distance image into multiple pixel groups based on distance intervals. Each pixel group contains pixels with distance values within a specific range. This segmentation allows different filter parameters to be applied to different distance ranges, enabling tailored noise reduction that prevents noise amplification and defective pixel increase.
Solution Approach 2:
The patent applies different filter parameters to different pixel groups based on their distance intervals. Close-range pixel groups use one set of filter parameters while far-range pixel groups use another set. This local differentiation optimizes noise reduction for each distance range without causing the harmful side effects of uniform filtering.
2Device complexity
If uniform filter parameters are applied to all pixels in distance image, then processing is simplified, but noise reduction effectiveness decreases
Solution Approach 1:
The patent segments the distance image into multiple pixel groups based on distance intervals, allowing different filter parameters to be applied to each group. This segmentation improves noise reduction effectiveness by adapting to the characteristics of different distance ranges while maintaining manageable processing complexity through systematic organization.
Solution Approach 2:
The patent changes filter parameters based on distance intervals. Different pixel groups receive different filter parameters optimized for their specific distance ranges. This parameter differentiation significantly improves noise reduction effectiveness compared to uniform filtering, while the systematic approach keeps processing complexity acceptable.
Data Source
AI summary
An input interface acquires a first distance image including a plurality of pixels, each of the plurality of pixels indicating a distance value from an image capture device to each point of an object. An image divider divides the first distance image into a plurality of pixel groups based on the distance values of the pixels, such that each of the plurality of pixel groups includes pixels having distance values falling within one of a plurality of distance intervals different from each other. A noise filter individually processes the plurality of pixel groups using a plurality of filter parameters different for the plurality of pixel groups, to reduce noises in the plurality of pixel groups. An image combiner combines the plurality of pixel groups processed by the noise filter, with each other, to generate a second distance image.