Improving Non-Local Video Denoising with Local Binary Patterns and Image Quantization

Author(s)

Contato, Welinton A. ; Nazare, Tiago S. ; Paranhos da Costa, Gabriel B. ; Ponti, Moacir ; Batista Neto, Joao E. S. ; IEEE

• Document type: Journal article
• Source: 2016 29TH SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI); v. N/A, p. 8-pg., 2016-01-01.

Abstract

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. (AU)

• FAPESP's process: 15/05310-3 - Representation Learning of spatio-temporal features from video
• Grantee: Gabriel de Barros Paranhos da Costa
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 14/21888-2 - Analysis of surface structures from videos of low energy electron microscopy
• Grantee: Welinton Andrey Contato
• Support Opportunities: Scholarships in Brazil - Master
• FAPESP's process: 15/04883-0 - Unusual event detection in surveillance videos
• Grantee: Tiago Santana de Nazare
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)