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

Washington

書目名稱Combating Bad Weather Part II影響因子(影響力)




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書目名稱Combating Bad Weather Part II被引頻次




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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

牙齒

喪失

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

考古學(xué)

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

橫截,橫斷

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

細(xì)微的差異

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