4DCAF: A temporal approach for denoising hyperspectral image sequences

作者：

Highlights：

• Adaptation of cellular automata (CA) based structures for the denoising of hyperspectral images sequences.

• The adaptation of the CA to properly perform the denoising considering a particular type of noise model is carried out by an evolutionary technique.

• Versatility for adjusting the rule set of the CA filtering structure in an automatic manner.

• Potential of the method for efficient parallel implementations.

• Performances are very good when compared to alternative state of the art filtering strategies.

摘要

•Adaptation of cellular automata (CA) based structures for the denoising of hyperspectral images sequences.•The adaptation of the CA to properly perform the denoising considering a particular type of noise model is carried out by an evolutionary technique.•Versatility for adjusting the rule set of the CA filtering structure in an automatic manner.•Potential of the method for efficient parallel implementations.•Performances are very good when compared to alternative state of the art filtering strategies.

论文关键词：Hyperspectral,Temporal denoising,Cellular automata,4DCAF

论文评审过程：Received 31 January 2017, Revised 15 June 2017, Accepted 25 July 2017, Available online 25 July 2017, Version of Record 17 August 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.07.023