Titlebook: Combating Bad Weather Part II; Fog Removal from Ima Sudipta Mukhopadhyay,Abhishek Kumar Tripathi Book 2015 Springer Nature Switzerland AG 2

Washington

书目名称Combating Bad Weather Part II影响因子(影响力)




书目名称Combating Bad Weather Part II影响因子(影响力)学科排名




书目名称Combating Bad Weather Part II网络公开度




书目名称Combating Bad Weather Part II网络公开度学科排名




书目名称Combating Bad Weather Part II被引频次




书目名称Combating Bad Weather Part II被引频次学科排名




书目名称Combating Bad Weather Part II年度引用




书目名称Combating Bad Weather Part II年度引用学科排名




书目名称Combating Bad Weather Part II读者反馈




书目名称Combating Bad Weather Part II读者反馈学科排名

barium-study

https://doi.org/10.1057/9780230512795algorithm outperforms prior state of the art algorithms in terms of contrast gain, percentage of the number of saturated pixels and computation time. The presented algorithm is independent of the density of the fog and does not require user intervention. It can handle color as well as gray images. A

牙齿

丧失

Conclusions and Future Directions,algorithm outperforms prior state of the art algorithms in terms of contrast gain, percentage of the number of saturated pixels and computation time. The presented algorithm is independent of the density of the fog and does not require user intervention. It can handle color as well as gray images. A

考古学

Book 2015eveloped. The presented fog removal algorithm uses new dark channel assumption and anisotropic diffusion for the initialization and refinement of the airlight map, respectively. Use of anisotropic diffusion helps to estimate the better airlight map estimation. The said fog removal algorithm requires

Small-Intestine

Single-Image Fog Removal Using an Anisotropic Diffusion,

Small-Intestine

横截,横断

1559-8136 nt of the airlight map, respectively. Use of anisotropic diffusion helps to estimate the better airlight map estimation. The said fog removal algorithm requires978-3-031-01124-5978-3-031-02252-4Series ISSN 1559-8136 Series E-ISSN 1559-8144

细微的差异

1559-8136 resent, there is no algorithm that is specifically designed for the removal of fog from videos. Application of a single-image fog removal algorithm over each video frame is a time-consuming and costly affair. It is demonstrated that with the intelligent use of temporal redundancy, fog removal algori

折磨

Book 2015ere is no algorithm that is specifically designed for the removal of fog from videos. Application of a single-image fog removal algorithm over each video frame is a time-consuming and costly affair. It is demonstrated that with the intelligent use of temporal redundancy, fog removal algorithms desig