Patch-based information reconstruction of cloud-contaminated multitemporal images

Chao-Hung Lin, Kang Hua Lai, Zhi Bin Chen, Jyun Yuan Chen

Research output: Contribution to journalArticlepeer-review

57 Citations (Scopus)

Abstract

Cloud covers, which are generally present in optical remote sensing images, limit the usage of acquired images and increase the difficulty in data analysis. Thus, information reconstruction of cloud-contaminated images generally plays an important role in image analysis. This paper proposes a novel method to reconstruct cloud-contaminated information in multitemporal remote sensing images. Based on the concept of utilizing temporal correlation of multitemporal images, we propose a patch-based information reconstruction algorithm that spatiotemporally segments a sequence of images into clusters containing several spatially connected components called patches and then clones information from cloud-free and high-similarity patches to their corresponding cloud-contaminated patches. In addition, a seam that passes through homogenous regions is used in information reconstruction to reduce radiometric inconsistency, and information cloning is solved using an optimization process with the determined seam. These processes enable the proposed method to well reconstruct missing information. Qualitative analyses of image sequences acquired by a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor and a quantitative analysis of simulated data with various cloud contamination conditions are conducted to evaluate the proposed method. The experimental results demonstrate the superiority of the proposed method to related methods in terms of radiometric accuracy and consistency, particularly for large clouds in a heterogeneous landscape.

Original languageEnglish
Article number6451247
Pages (from-to)163-174
Number of pages12
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume52
Issue number1
DOIs
Publication statusPublished - 2014 Jan 1

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

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