Publication de 12 numéros par an
ISSN Imprimer: 0040-2508
ISSN En ligne: 1943-6009
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DCT-BASED DENOISING IN MULTICHANNEL IMAGING WITH REFERENCE
RÉSUMÉ
A task of denoising of a component image of multichannel data is considered in this paper assuming that a reference (noise-free) image is available. We propose a denoising approach based on three-dimensional (3D) discrete cosine transform (DCT) applied in blocks. We show that a use of a reference image allows improving the denoising performance (measured by different quality metrics) although it depends on several factors such as a choice of the reference and the way it is pre-processed. One of the most important requirements to achieve a good performance is a similarity between to be processed and the reference images. A high cross-correlation between them is a necessary but not sufficient condition. These images should have also close dynamic range. If all these requirements are satisfied by an appropriate choice or by pre-processing of the reference, improvements of the metrics PSNR and PSNR-HVS-M can be up to 3...5 dB compared to the component-wise DCT-based image denoising. We also analyze and process real-life hyperspectral images and provide examples showing efficiency of filtering noisy component images using other components with high signal-to-noise ratios as references.
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Stanković Ljubiša, Daković Miloš, Compressive Sensing Inspired Multivariate Median, Circuits, Systems, and Signal Processing, 38, 5, 2019. Crossref
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Abramov Sergey, Uss Mikhail, Lukin Vladimir, Vozel Benoit, Chehdi Kacem, Egiazarian Karen, Enhancement of Component Images of Multispectral Data by Denoising with Reference, Remote Sensing, 11, 6, 2019. Crossref