Sparse representation of images using substitution of wavelet by patches

Salima Hassairi; Intidhar Jemel; Ridha Ejbali; Mourad Zaied

doi:10.1117/12.2558680

31 January 2020 Sparse representation of images using substitution of wavelet by patches

Salima Hassairi, Intidhar Jemel, Ridha Ejbali, Mourad Zaied

Proceedings Volume 11433, Twelfth International Conference on Machine Vision (ICMV 2019); 114331H (2020) https://doi.org/10.1117/12.2558680
Event: Twelfth International Conference on Machine Vision, 2019, Amsterdam, Netherlands

Abstract

Classical signal representation techniques generally use a description of the components on a basis on which the representation of the signal is unique such as wavelets network. Conversely, sparse representations consist in the decomposition of the signal on a dictionary comprising a number of elements much larger than the dimension of the signal. This technique can be widely used for representation, compression, denoising and separation of all types of signals. Consequently, some researches have confirmed that the use of a predefined dictionary is less efficient than a dictionary from training data. So, the idea of this paper is to propose a new technique for the creation of a dictionary using the wavelet decomposition to enhance the sparse representation of images. This technique is based on the combination of sparse coding and the fast wavelet transform algorithms for image representation. Our results obtained using different universal image databases showed greater performances in the representation of images when compared to some methods from the state of the art.

Citation Download Citation

Salima Hassairi, Intidhar Jemel, Ridha Ejbali, and Mourad Zaied "Sparse representation of images using substitution of wavelet by patches", Proc. SPIE 11433, Twelfth International Conference on Machine Vision (ICMV 2019), 114331H (31 January 2020); https://doi.org/10.1117/12.2558680

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