کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1535752 | 1512632 | 2013 | 8 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Infrared surveillance image super resolution via group sparse representation Infrared surveillance image super resolution via group sparse representation](/preview/png/1535752.png)
Infrared (IR) surveillance image generally has low resolution and signal-to-noise ratios. In this paper, we present a new approach to IR image super resolution via group sparse representation (GS). First based on IR image feature, an algorithm of combining the group orthogonal matching pursuit and K-SVD is proposed to train the dictionaries. The dictionary training can ensure that the corresponding low resolution (LR) and high resolution (HR) image have same GS coefficients. Then the group sparse coefficients of the input LR image are sought to reconstruct the HR image with the trained LR and HR dictionary pair. Experimental results indicate that our method generates sharper results with higher Peak Signal to Noise Ratio (PSNR), and is more robust to noise than several popular methods.
Journal: Optics Communications - Volume 289, 15 February 2013, Pages 45–52