A Video Super Resolution Algorithm Based on Wavelet Coefficient

Abstract:

In this paper, we propose a new super-resolution algorithm based on wavelet coefficient. The proposed algorithm uses discrete wavelet transform (DWT) to decompose the input low-resolution image sequences into four subband images, including LL, LH, HL, HH. Then the input images have been processed by the 3DSKR (Three Dimensional Steering Kernel Regression) super resolution (SR) algorithm, and the result replaces the LL subband image, while the three high-frequency subband images have been interpolated. Finally, combining all these images to generate a new high-resolution image by using inverse DWT. Proposed method has been verified on Calendar and Foliage by Matlab software platform. The peak signal-to-noise (PSNR), structural similarity (SSIM) and visual results are compared, and show that the computational complexity of the proposed algorithm decline by 30 percent compared with the existing algorithm to obtain the approximate results.

• Periodical: Applied Mechanics and Materials (Volume 610)
• Pages: 425-428
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.610.425
• Online since: August 2014
• Authors: Wei Jian Liu, Si Da Xiao, Ruo He Yao*
• Keywords: Discrete Wavelet Transform, Image Enhancement, Interpolation, Super Resolution

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