An Improved Haze Removal Method for the Application of Geo- Graphical Data Analysis. | [Pakistan Journal of Biotechnology • 2018]

Author(s):

1. Anju J Prakash: Deptartment of Computer Science and Engineering, Noorul Islam University, India

2. A Ferdin: Deptartment of Computer Science and Engineering, Noorul Islam University, India

3. Christopher: Deptartment of Computer Science and Engineering, Noorul Islam University, India

Abstract:

The images taken in ghastly climatic conditions is a lot tainted owing to the occurrence of haze. It may also affect heavily, such images used in the ground of computer visualization, object recognition etc. As an aim to resolve this problem in this paper a better image enhancement as well as classification method is employed. The projected work takes benefit of SVD as this solo value allow us to characterize the picture with a minimal set of value that shrink storage space and progress the quality. For a superior quality and feature improvement a rate-based alteration is completed with the help of gaussian filter. The eventual dehazed image is then classified using an improved knn as part of geographical data analysis.

Page(s): 903-907

DOI: DOI not available

Published: Journal: Pakistan Journal of Biotechnology, Volume: 15, Issue: 4, Year: 2018

Keywords:

Keywords are not available for this article.

References:

[1] Ancuti , C.O.,C.Ancuti, 2013.Single image dehazing by multi-scale fusion,IEEE Trans. Image Process 22 3271 -3282

[2] Arunkumar R.,NagrajBalakrishnan,:, 2017.Medical image classification for disease diagnosis by DBN methods,Pak. J. Biotechnol 14 -

[3] ChangLiu and Zhaowei Shang, 2016.An adaptive tone mapping algorithm based on gaussian filter,IEEE International conference on cloud Computing and big data -

[4] Fattal , R., 2008.Single image dehazing,ACM Transactions on Graphics (TOG) 27 72 -

[5] Fern´andez F . and P.,Isasi, 2008.Local feature weighting in nearest prototype classification,IEEE Transactions on Neural Networks 19 40 -53

[6] Fix , E.,J.L.Hodges,DiscriminatoryAnalysis, 1951.,Randolf Field Texas Pp 238 247 -

[7] Fukunaga , K., 1990., -

[8] .An improved haze removal ……, -

[9] He , Kaiming, Jian Sun and Xiaoou,Tang, 2011.Single image haze removal using dark channel prior,IEEE Transactions on Pattern Analysis and Machine Intelligence 33 2341 -2353

[10] KaimingHe, 2013.Jian Sun and Xiaou Tang, Guided Image Filtering,IEEE Transactions on Pattern Analysis and Machine Intelligence 35 1397 -1409

[11] Kopf , J., 2008.Deep photo: Model-based photograph enhancement and viewing,ACM Trans. Graph 27 116 -10

[12] Li , W.J.,Gu , B.,Huang , J.T., 2012.Single image visibility enhancement in gradient domain,IET Image Process 6 589 -595

[13] Narasimhan S.G. and S.K Nayar, 2003.Contrast restoration of weather degraded images,IEEE Trans.pattern Anal. Mach. Intell 25 713 -724

[14] RannanFattal, 2008.Single Image Dehazing,ACM Transactions on Graphics (TOG) 27: 72 -

[15] Schechner , Y.Y., S.G.,Narasimhan and S.K.,Nayar, 2003.,Polarization based vision through haze Appl. Opt 42 511 -525

[16] Tan , R.T., 2008.Visibility in Bad Weather from a Single Image,Proceedings IEEE Conference on Computer Vision Pattern Recognitions 1 -8

[17] Tarel , J.P. and N.,Hautiere, 2009.Fast visibility restoration from a single color or gray level image,IEEE 12th Int. Conf. on Computer Vision 2201 2208 -

[18] Xu , H.,J.Guo,Q.Liu,L.Ye, 2012.Fast image dehazing using improved dark channel prior,Proc. IEEE Int. Conf. Inf. Sci. Techno 663 667 -

[19] ZetianMi,MinghuiWang, 2016.Single image dehazing via multi-scale gradient domain contrast enhancement,IET Image Process 10 206 -214

Citations

Downloads

Views