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).
    @inproceedings{c2657ac489a84f45b554a3959d838a7b,
    title = "High quality infrared images with novel algorithm for multi-noises removal",
    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.",
    keywords = "Gaussian noise, IR, Impulse noise, MSE, MSSIM, PSNR, Poisson noise",
    author = "Xu Huang and Islam, {Sheikh Md. Rabiul} and Mingyu Liao and Shutao Li",
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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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    AU - Islam, Sheikh Md. Rabiul

    AU - Liao, Mingyu

    AU - Li, Shutao

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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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    KW - Impulse noise

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    KW - PSNR

    KW - Poisson noise

    M3 - Conference contribution

    SN - 9789881925299

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    T3 - Lecture Notes in Computer Science LNCS

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    BT - Proceedings of The World Congress on Engineering : WCE 2013

    PB - Springer

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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).