A conditional random field model for context aware cloud detection in sky images

Research output: Contribution to journalArticlepeer-review

Abstract

A conditional random field (CRF) model for cloud detection in ground based sky images is presented. We show that very high cloud detection accuracy can be achieved by combining a discriminative classifier and a higher order clique potential in a CRF framework. The image is first divided into homogeneous regions using a mean shift clustering algorithm and then a CRF model is defined over these regions. The various parameters involved are estimated using training data and the inference is performed using Iterated Conditional Modes (ICM) algorithm. We demonstrate how taking spatial context into account can boost the accuracy. We present qualitative and quantitative results to prove the superior performance of this framework in comparison with other methods applied for cloud detection.

Original languageEnglish (US)
JournalUnknown Journal
StatePublished - Jun 18 2019

Keywords

  • Cloud detection
  • Conditional random field
  • Context aware segmentation
  • Ground based sky image

ASJC Scopus subject areas

  • General

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