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Volume 39 Issue 2
Dec.  2014
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High quality infrared video image restoration algorithm based on the improved ridgelet transform

  • Received Date: 2014-02-16
    Accepted Date: 2014-04-11
  • In order to reconstruct high quality infrared video images from the degraded images, an image restoration algorithm was adopted based on the improved ridge wavelet transform. Firstly, the ridge wavelet transform was carried out for the degraded images. Then, one weighted improved adaptive pseudo median filtering algorithm was used to process the ridge wave coefficients. Finally, adaptive Wiener filtering algorithm was introduced to suppress for "wrap around" effect of images after filtering. After theoretical analysis and experimental verification, the relevant simulated degraded images, the real degraded images and the peak signal to noise ratio were obtained. The results show that the algorithm in this paper is superior to the algorithms, such as the pseudo median filtering and two types of ridge wavelet transform denoising algorithms. The study is helpful for the research of infrared video degraded image restoration.
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通讯作者: 陈斌, bchen63@163.com
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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High quality infrared video image restoration algorithm based on the improved ridgelet transform

  • 1. Department of Computer Engineering, Sichuan Vocational and Technical College of Communications, Chengdu 611130, China

Abstract: In order to reconstruct high quality infrared video images from the degraded images, an image restoration algorithm was adopted based on the improved ridge wavelet transform. Firstly, the ridge wavelet transform was carried out for the degraded images. Then, one weighted improved adaptive pseudo median filtering algorithm was used to process the ridge wave coefficients. Finally, adaptive Wiener filtering algorithm was introduced to suppress for "wrap around" effect of images after filtering. After theoretical analysis and experimental verification, the relevant simulated degraded images, the real degraded images and the peak signal to noise ratio were obtained. The results show that the algorithm in this paper is superior to the algorithms, such as the pseudo median filtering and two types of ridge wavelet transform denoising algorithms. The study is helpful for the research of infrared video degraded image restoration.

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