Noise Reduction of Depth Cameras Images Based on Deep Neural Network

Today, infrared sensors or depth sensors are widely used to control applications, games, information acquisition, dynamic and static 3D scenes. Despite the widespread use of these images, their quality is limited to low-quality images, as the infrared sensor does not have high resolution and the ima...

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Main Authors: Alireza Ghasemi, Mohsen Ashourian
Format: Article
Language:English
Published: OICC Press 2024-02-01
Series:Majlesi Journal of Electrical Engineering
Subjects:
Online Access:https://oiccpress.com/mjee/article/view/4887
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author Alireza Ghasemi
Mohsen Ashourian
author_facet Alireza Ghasemi
Mohsen Ashourian
author_sort Alireza Ghasemi
collection DOAJ
description Today, infrared sensors or depth sensors are widely used to control applications, games, information acquisition, dynamic and static 3D scenes. Despite the widespread use of these images, their quality is limited to low-quality images, as the infrared sensor does not have high resolution and the images produced by it have noise. Therefore, given the problems and the importance of using 3-D images, the quality of these images should be improved in order to provide accurate images from depth cameras. In this paper, the noise reduction of depth images using convolutional neural networks is considered. A convolutional neural network with a depth of 20 and three layers and a pre-trained neural network is used. We developed the system and tested its performance for two datasets of depth and color images, Middlebury and EURECOM Kinect Face. Results show that for EURECOM Kinect Face images, PSNR improvement is approximately 8 to 15 dB and for Middlebury images the PSNR improvement is about 5 to 14 dB.
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issn 2345-377X
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language English
publishDate 2024-02-01
publisher OICC Press
record_format Article
series Majlesi Journal of Electrical Engineering
spelling doaj-art-0f55ec3b6e49424398e4e4c1a80d5a8d2025-08-20T02:43:38ZengOICC PressMajlesi Journal of Electrical Engineering2345-377X2345-37962024-02-0114310.29252/mjee.14.3.12Noise Reduction of Depth Cameras Images Based on Deep Neural NetworkAlireza GhasemiMohsen AshourianToday, infrared sensors or depth sensors are widely used to control applications, games, information acquisition, dynamic and static 3D scenes. Despite the widespread use of these images, their quality is limited to low-quality images, as the infrared sensor does not have high resolution and the images produced by it have noise. Therefore, given the problems and the importance of using 3-D images, the quality of these images should be improved in order to provide accurate images from depth cameras. In this paper, the noise reduction of depth images using convolutional neural networks is considered. A convolutional neural network with a depth of 20 and three layers and a pre-trained neural network is used. We developed the system and tested its performance for two datasets of depth and color images, Middlebury and EURECOM Kinect Face. Results show that for EURECOM Kinect Face images, PSNR improvement is approximately 8 to 15 dB and for Middlebury images the PSNR improvement is about 5 to 14 dB.https://oiccpress.com/mjee/article/view/4887Convolution neural networksDepth Camera ImagesImage EnhancementNoise Reduction
spellingShingle Alireza Ghasemi
Mohsen Ashourian
Noise Reduction of Depth Cameras Images Based on Deep Neural Network
Majlesi Journal of Electrical Engineering
Convolution neural networks
Depth Camera Images
Image Enhancement
Noise Reduction
title Noise Reduction of Depth Cameras Images Based on Deep Neural Network
title_full Noise Reduction of Depth Cameras Images Based on Deep Neural Network
title_fullStr Noise Reduction of Depth Cameras Images Based on Deep Neural Network
title_full_unstemmed Noise Reduction of Depth Cameras Images Based on Deep Neural Network
title_short Noise Reduction of Depth Cameras Images Based on Deep Neural Network
title_sort noise reduction of depth cameras images based on deep neural network
topic Convolution neural networks
Depth Camera Images
Image Enhancement
Noise Reduction
url https://oiccpress.com/mjee/article/view/4887
work_keys_str_mv AT alirezaghasemi noisereductionofdepthcamerasimagesbasedondeepneuralnetwork
AT mohsenashourian noisereductionofdepthcamerasimagesbasedondeepneuralnetwork