TY - GEN
T1 - Comments on randomly sampled non local means image filter
AU - Pardo, Alvaro
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2014.
PY - 2014
Y1 - 2014
N2 - In this work we comment the results presented in [1] regarding a random sampling approach of the Non Local Means (NLM) image denoising filter with respect to computational cost and denoising performance. We will show that although the approach is novel and mathematically revealing, the computation cost of the approach is higher, and the PSNR lower, compared to the classical version. Furthermore, we will present a probabilistic model to evaluate the performance of different versions of NLM and tune its parameters.
AB - In this work we comment the results presented in [1] regarding a random sampling approach of the Non Local Means (NLM) image denoising filter with respect to computational cost and denoising performance. We will show that although the approach is novel and mathematically revealing, the computation cost of the approach is higher, and the PSNR lower, compared to the classical version. Furthermore, we will present a probabilistic model to evaluate the performance of different versions of NLM and tune its parameters.
UR - http://www.scopus.com/inward/record.url?scp=84949135682&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-12568-8_61
DO - 10.1007/978-3-319-12568-8_61
M3 - Contribución a la conferencia
AN - SCOPUS:84949135682
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 498
EP - 505
BT - Progress in Pattern Recognition Image Analysis, Computer Vision and Applications - 19th Iberoamerican Congress, CIARP 2014, Proceedings
A2 - Bayro-Corrochano, Eduardo
A2 - Hancock, Edwin
PB - Springer Verlag
T2 - 19th Iberoamerican Congress on Pattern Recognition, CIARP 2014
Y2 - 2 November 2014 through 5 November 2014
ER -