TY - GEN
T1 - Image filter based on block matching, discrete cosine transform and principal component analysis
AU - Callejas Ramos, Alejandro I.
AU - Felipe-Riveron, Edgardo M.
AU - Manrique Ramirez, Pablo
AU - Pogrebnyak, Oleksiy
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - An algorithm for filtering the images contaminated by additive white Gaussian noise is proposed. The algorithm uses the groups of Hadamard transformed patches of discrete cosine coefficients to reject noisy components according to Wiener filtering approach. The groups of patches are found by the proposed block similarity search algorithm of reduced complexity performed on block patches in transform domain. When the noise variance is small, the proposed filter uses an additional stage based on principal component analysis; otherwise the experimental Wiener filtering is performed. The obtained filtering results are compared to the state of the art filters in terms of peak signal-to-noise ratio and structure similarity index. It is shown that the proposed algorithm is competitive in terms of signal to noise ratio and almost in all cases is superior to the state of the art filters in terms of structure similarity.
AB - An algorithm for filtering the images contaminated by additive white Gaussian noise is proposed. The algorithm uses the groups of Hadamard transformed patches of discrete cosine coefficients to reject noisy components according to Wiener filtering approach. The groups of patches are found by the proposed block similarity search algorithm of reduced complexity performed on block patches in transform domain. When the noise variance is small, the proposed filter uses an additional stage based on principal component analysis; otherwise the experimental Wiener filtering is performed. The obtained filtering results are compared to the state of the art filters in terms of peak signal-to-noise ratio and structure similarity index. It is shown that the proposed algorithm is competitive in terms of signal to noise ratio and almost in all cases is superior to the state of the art filters in terms of structure similarity.
KW - Block matching
KW - Image filtering
KW - Principal component analysis
UR - http://www.scopus.com/inward/record.url?scp=85028461818&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-62434-1_34
DO - 10.1007/978-3-319-62434-1_34
M3 - Contribución a la conferencia
SN - 9783319624334
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 414
EP - 424
BT - Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings
A2 - Herrera-Alcantara, Oscar
A2 - Sidorov, Grigori
PB - Springer Verlag
T2 - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016
Y2 - 23 October 2016 through 28 October 2016
ER -