Fusion of Thresholding Rules During Wavelet-Based Noisy Image Compression

Bekhtin, Yury S.; Lupachev, Alexander; Titov, D. V.; Siryamkin, Vladimir

doi:10.1051/matecconf/20167901072

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Related Work On the Compression Of Noisy Images And Enhancem...1

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2023

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“…A new method for combining semi-soft thresholding rules during image compression with multiplicative noise based on wavelets is suggested by Yury Bekhtin et al [22]. The method chooses the best thresholding rule and the threshold value using the proposed criteria which provide the best nonlinear approximations and take into account the quantization errors.…”

Section: Related Work On the Compression Of Noisy Images And Enhancem...mentioning

confidence: 99%

Exploitation of second-and fourth-order PDEs to improve Lossy compression of noisy images

Welba¹,

THIERRY²,

Noura³

et al. 2023

Phys. Scr.

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This paper presents a lossy compression method for noisy images. The main contributions in this paper are : improve the performance of noisy image compression algorithms by using partial differential equations (PDEs) as an image preprocessing filter and show that it is more advantageous to apply a restoration filter before compressing noise images.Method :The preprocessing filter is applied to the noisy image first. A comparing of the obtained outcomes with those in the scientific literature devoted to the restoration of noisy images is performed. The filtered image is then submitted to a compression algorithm. The compression algorithm employed is a hybrid of the following : DWT+SPIHT+HUFFMAN. Results:The simulation results demonstrate that the suggested technique is as efficient as approaches described in the scientific literature for picture compression and/or image restoration.

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Section: Related Work On the Compression Of Noisy Images And Enhancem...mentioning

confidence: 99%