%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/07.12.19.12
%2 sid.inpe.br/sibgrapi/2016/07.12.19.12.33
%@doi 10.1109/SIBGRAPI.2016.041
%T Improving Non-Local Video Denoising with Local Binary Patterns and Image Quantization
%D 2016
%A Contato, Welinton Andrey,
%A Nazare, Tiago Santana,
%A Paranhos da Costa, Gabriel de Barros,
%A Ponti, Moacir,
%A Batista Neto, João do Espirito Santo,
%@affiliation Instituto de Ciências Matemáticas e de Computação - USP
%@affiliation Instituto de Ciências Matemáticas e de Computação - USP
%@affiliation Instituto de Ciências Matemáticas e de Computação - USP
%@affiliation Instituto de Ciências Matemáticas e de Computação - USP
%@affiliation Instituto de Ciências Matemáticas e de Computação - USP
%E Aliaga, Daniel G.,
%E Davis, Larry S.,
%E Farias, Ricardo C.,
%E Fernandes, Leandro A. F.,
%E Gibson, Stuart J.,
%E Giraldi, Gilson A.,
%E Gois, João Paulo,
%E Maciel, Anderson,
%E Menotti, David,
%E Miranda, Paulo A. V.,
%E Musse, Soraia,
%E Namikawa, Laercio,
%E Pamplona, Mauricio,
%E Papa, João Paulo,
%E Santos, Jefersson dos,
%E Schwartz, William Robson,
%E Thomaz, Carlos E.,
%B Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)
%C São José dos Campos, SP, Brazil
%8 4-7 Oct. 2016
%I IEEE Computer Society´s Conference Publishing Services
%J Los Alamitos
%S Proceedings
%K local binary patterns, most significant bits, non-local means, video denoising.
%X The most challenging aspect of video and image denoising is to preserve texture and small details, while filtering out noise. To tackle such problem, we present two novel variants of the 3D Non-Local Means (NLM3D) which are suitable for videos and 3D images. The first proposed algorithm computes texture patterns for each pixel by using the LBP-TOP descriptor to modify the NLM3D weighting function. It also uses MSB (Most Significant Bits) quantization to improve robustness to noise. The second proposed algorithm filters homogeneous and textured regions differently. It analyses the percentage of non-uniform LBP patterns of a region to determine whether or not the region exhibits textures and/or small details. Quantitative and qualitative experiments indicate that the proposed approaches outperform well known methods for the video denoising task, especially in the presence of textures and small details.
%@language en
%3 PID4356503.pdf