We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
An Improved Defocus Blur with Combined Local Binary Patterns and Nearest Neighbour Technique.
- Authors
Sravani, A. Jyothi; Prasad, L. V. Narasimha
- Abstract
Defocus blur is one of the phenomena in obtaining images using optical imaging systems. Blur parts mainly segment images into obscure or non-obscure regions. The existing research on defocus blur addresses the individual techniques based removal of blur. The present paper focuses on fused technique with a combination of local binary and nearest neighbor. In this the roughness metrics based on Local binary patterns (LBP) with a respective algorithm that isolates the clear-cut image regions. Based on the local binary patterns, roughness metric in local images mentions blurry regions. Applying these metrics in combination with image matting and multi scale inference achieves extreme levels of roughness. When LBP is combined wit KNearest Neighbor (KNN) encompass a better outcome and also improves the efficiency of the segmentation with high-speed. This assures an improved treatment for blur images.
- Subjects
IMAGING systems; OPTICAL images; ALGORITHMS; IMAGE reconstruction; OBJECT recognition (Computer vision)
- Publication
International Journal of Simulation: Systems, Science & Technology, 2020, Vol 21, Issue 2, p1
- ISSN
1473-8031
- Publication type
Article
- DOI
10.5013/IJSSST.a.21.02.19