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Adaptive wavelet thresholding for image denoising using sure minimization and clustering of wavelet coefficients

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Fedak V., Nakonechnyy A.

Czasopismo Techniczne

Images and video are often coded using block-based discrete cosine transform (DCT) or discrete wavelet transform (DWT) which cause a great deal of visual distortions. In this paper, an extension of the intra-scale dependencies of wavelet coefficients is proposed to improve denoising performance. This method incorporates information on neighbouring wavelet coefficients that are inside of manually created clusters. Extensive experimental results are given to demonstrate the strength of the proposed method.

Adaptive trained filters with SSIM optimization for video upscaling with soft pixel value truncation

100%

Nakonechnyy A., Veres Z.

Czasopismo Techniczne

The paper presents the modified model for video upscaling based on the preservation of structural information from the input sequence in the adaptive trained filters. Additionally, it is proposed to make soft truncation of the result pixel value during the interpolation process. The evaluation of the proposed algorithm has shown good resulting for a variety of test sequences. The best results are obtained for a sequence with average bitrate and movement of the scene. Received results prove the algorithm is valuable for upscaling tasks.

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2 Czasopismo Techniczne

1 2016

1 2015

2 Nakonechnyy A.

1 Fedak V.

1 Veres Z.

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Adaptive wavelet thresholding for image denoising using sure minimization and clustering of wavelet coefficients

Adaptive trained filters with SSIM optimization for video upscaling with soft pixel value truncation