High quality infrared images with novel algorithm for multi-noises removal

Xu Huang, Sheikh Md. Rabiul Islam, Mingyu Liao, Shutao Li

Research output: A Conference proceeding or a Chapter in BookConference contribution

1 Citation (Scopus)

Abstract

Infrared (IR) images have been used extensively for military and civilian purposes, in particular in dark conditions. High quality images are particularly needed in various applications, especially for the security and military environments. But various images, including IR images, almost cannot avoid various noises when they were born as noise sources are distributed almost everywhere. In our paper, in order to obtain a good quality of IR image, it proposes a novel denoising algorithm based on Cohen-Daubechies-Feauveau wavelets with the low-pass filters of the length 9 and 7 (CDF 9/7) wavelet transform. We also first applied the lifting structure to improve the drawbacks of a traditional wavelet transform. As the normal wavelet transform seems to be restricted and limited a class of opportunities for multi-scale representation of multi-dimensional signals to estimate noises and then remove the noises from original images. The final simulation results show that our proposed algorithm in this paper is much efficient in estimating and reducing noises from the images contaminated by multi noises, such as Gaussian noise, Poisson noise, and impulse (Salt& pepper) noise. Experimental results on several tests for infrared images by using this algorithm are presented, for example under the noise with  = 0.2 and density = 20% cases, for mean square error (MSE) our method decreasing 83%; peak signal to noise ratio (PSNR) increasing 14% and mean of structural similarity (MSSIM) increasing 67% with the same conditions. Obviously, the results show our proposed algorithm significantly superior to other related methods.
Original languageEnglish
Title of host publicationProceedings of The World Congress on Engineering : WCE 2013
Place of PublicationUK
PublisherSpringer
Pages2184-2189
Number of pages6
VolumeIII
ISBN (Print)9789881925299
Publication statusPublished - 2013
EventWorld Congress on Engineering 2013 - London, London, United Kingdom
Duration: 3 Jul 20135 Jul 2013
http://www.iaeng.org/WCE2013/

Publication series

NameLecture Notes in Computer Science LNCS
PublisherSpringer
Volume3
ISSN (Print)2078-0958

Conference

ConferenceWorld Congress on Engineering 2013
CountryUnited Kingdom
CityLondon
Period3/07/135/07/13
Internet address

Fingerprint

Wavelet transforms
Infrared radiation
Low pass filters
Mean square error
Image quality
Signal to noise ratio
Salts

Cite this

Huang, X., Islam, S. M. R., Liao, M., & Li, S. (2013). High quality infrared images with novel algorithm for multi-noises removal. In Proceedings of The World Congress on Engineering : WCE 2013 (Vol. III, pp. 2184-2189). (Lecture Notes in Computer Science LNCS; Vol. 3). UK: Springer.
Huang, Xu ; Islam, Sheikh Md. Rabiul ; Liao, Mingyu ; Li, Shutao. / High quality infrared images with novel algorithm for multi-noises removal. Proceedings of The World Congress on Engineering : WCE 2013 . Vol. III UK : Springer, 2013. pp. 2184-2189 (Lecture Notes in Computer Science LNCS).
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abstract = "Infrared (IR) images have been used extensively for military and civilian purposes, in particular in dark conditions. High quality images are particularly needed in various applications, especially for the security and military environments. But various images, including IR images, almost cannot avoid various noises when they were born as noise sources are distributed almost everywhere. In our paper, in order to obtain a good quality of IR image, it proposes a novel denoising algorithm based on Cohen-Daubechies-Feauveau wavelets with the low-pass filters of the length 9 and 7 (CDF 9/7) wavelet transform. We also first applied the lifting structure to improve the drawbacks of a traditional wavelet transform. As the normal wavelet transform seems to be restricted and limited a class of opportunities for multi-scale representation of multi-dimensional signals to estimate noises and then remove the noises from original images. The final simulation results show that our proposed algorithm in this paper is much efficient in estimating and reducing noises from the images contaminated by multi noises, such as Gaussian noise, Poisson noise, and impulse (Salt& pepper) noise. Experimental results on several tests for infrared images by using this algorithm are presented, for example under the noise with  = 0.2 and density = 20{\%} cases, for mean square error (MSE) our method decreasing 83{\%}; peak signal to noise ratio (PSNR) increasing 14{\%} and mean of structural similarity (MSSIM) increasing 67{\%} with the same conditions. Obviously, the results show our proposed algorithm significantly superior to other related methods.",
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Huang, X, Islam, SMR, Liao, M & Li, S 2013, High quality infrared images with novel algorithm for multi-noises removal. in Proceedings of The World Congress on Engineering : WCE 2013 . vol. III, Lecture Notes in Computer Science LNCS, vol. 3, Springer, UK, pp. 2184-2189, World Congress on Engineering 2013, London, United Kingdom, 3/07/13.

High quality infrared images with novel algorithm for multi-noises removal. / Huang, Xu; Islam, Sheikh Md. Rabiul; Liao, Mingyu; Li, Shutao.

Proceedings of The World Congress on Engineering : WCE 2013 . Vol. III UK : Springer, 2013. p. 2184-2189 (Lecture Notes in Computer Science LNCS; Vol. 3).

Research output: A Conference proceeding or a Chapter in BookConference contribution

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N2 - Infrared (IR) images have been used extensively for military and civilian purposes, in particular in dark conditions. High quality images are particularly needed in various applications, especially for the security and military environments. But various images, including IR images, almost cannot avoid various noises when they were born as noise sources are distributed almost everywhere. In our paper, in order to obtain a good quality of IR image, it proposes a novel denoising algorithm based on Cohen-Daubechies-Feauveau wavelets with the low-pass filters of the length 9 and 7 (CDF 9/7) wavelet transform. We also first applied the lifting structure to improve the drawbacks of a traditional wavelet transform. As the normal wavelet transform seems to be restricted and limited a class of opportunities for multi-scale representation of multi-dimensional signals to estimate noises and then remove the noises from original images. The final simulation results show that our proposed algorithm in this paper is much efficient in estimating and reducing noises from the images contaminated by multi noises, such as Gaussian noise, Poisson noise, and impulse (Salt& pepper) noise. Experimental results on several tests for infrared images by using this algorithm are presented, for example under the noise with  = 0.2 and density = 20% cases, for mean square error (MSE) our method decreasing 83%; peak signal to noise ratio (PSNR) increasing 14% and mean of structural similarity (MSSIM) increasing 67% with the same conditions. Obviously, the results show our proposed algorithm significantly superior to other related methods.

AB - Infrared (IR) images have been used extensively for military and civilian purposes, in particular in dark conditions. High quality images are particularly needed in various applications, especially for the security and military environments. But various images, including IR images, almost cannot avoid various noises when they were born as noise sources are distributed almost everywhere. In our paper, in order to obtain a good quality of IR image, it proposes a novel denoising algorithm based on Cohen-Daubechies-Feauveau wavelets with the low-pass filters of the length 9 and 7 (CDF 9/7) wavelet transform. We also first applied the lifting structure to improve the drawbacks of a traditional wavelet transform. As the normal wavelet transform seems to be restricted and limited a class of opportunities for multi-scale representation of multi-dimensional signals to estimate noises and then remove the noises from original images. The final simulation results show that our proposed algorithm in this paper is much efficient in estimating and reducing noises from the images contaminated by multi noises, such as Gaussian noise, Poisson noise, and impulse (Salt& pepper) noise. Experimental results on several tests for infrared images by using this algorithm are presented, for example under the noise with  = 0.2 and density = 20% cases, for mean square error (MSE) our method decreasing 83%; peak signal to noise ratio (PSNR) increasing 14% and mean of structural similarity (MSSIM) increasing 67% with the same conditions. Obviously, the results show our proposed algorithm significantly superior to other related methods.

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SN - 9789881925299

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Huang X, Islam SMR, Liao M, Li S. High quality infrared images with novel algorithm for multi-noises removal. In Proceedings of The World Congress on Engineering : WCE 2013 . Vol. III. UK: Springer. 2013. p. 2184-2189. (Lecture Notes in Computer Science LNCS).