A Framework for Quality Enhancement of Multispectral Remote Sensing Images

Shilpa Suresh; Devikalyan Das; Shyam Lal

doi:10.1109/ICoAC.2017.8441181

A Framework for Quality Enhancement of Multispectral Remote Sensing Images

Shilpa Suresh, Devikalyan Das, Shyam Lal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

Researches in satellite image enhancement have been particularly confined to two major areas-contrast enhancement and image de noising of remote sensing images. The processing of relatively dark or shadowed images necessitates the need for robust remote sensing enhancement techniques. In this paper, a robust framework for quality enhancement of multispectral remote sensing images is proposed. The quantitative results of proposed algorithm and other existing remote sensing enhancement algorithms are calculated in terms of DE, NIQMC, BIQME, PisDist and CM on different remote sensing and other image databases. Results reveal that visual enhancement of the proposed algorithm is better than other existing remote sensing enhancement algorithms. Finally, the simulation experimental results show that proposed algorithm is effective and efficient for remotes sensing as well as natural images.

Original language	English
Title of host publication	2017 9th International Conference on Advanced Computing, ICoAC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	9-14
Number of pages	6
ISBN (Print)	9781538643495
DOIs	https://doi.org/10.1109/ICoAC.2017.8441181
Publication status	Published - 20-08-2018
Event	9th International Conference on Advanced Computing, ICoAC 2017 - Chennai, India Duration: 14-12-2017 → 16-12-2017

Publication series

Name	2017 9th International Conference on Advanced Computing, ICoAC 2017

Conference

Conference	9th International Conference on Advanced Computing, ICoAC 2017
Country/Territory	India
City	Chennai
Period	14-12-17 → 16-12-17

All Science Journal Classification (ASJC) codes

Health Informatics
Artificial Intelligence
Computer Networks and Communications
Computer Science Applications
Information Systems and Management

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10.1109/ICoAC.2017.8441181

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Suresh, S., Das, D., & Lal, S. (2018). A Framework for Quality Enhancement of Multispectral Remote Sensing Images. In 2017 9th International Conference on Advanced Computing, ICoAC 2017 (pp. 9-14). Article 8441181 (2017 9th International Conference on Advanced Computing, ICoAC 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICoAC.2017.8441181

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title = "A Framework for Quality Enhancement of Multispectral Remote Sensing Images",

abstract = "Researches in satellite image enhancement have been particularly confined to two major areas-contrast enhancement and image de noising of remote sensing images. The processing of relatively dark or shadowed images necessitates the need for robust remote sensing enhancement techniques. In this paper, a robust framework for quality enhancement of multispectral remote sensing images is proposed. The quantitative results of proposed algorithm and other existing remote sensing enhancement algorithms are calculated in terms of DE, NIQMC, BIQME, PisDist and CM on different remote sensing and other image databases. Results reveal that visual enhancement of the proposed algorithm is better than other existing remote sensing enhancement algorithms. Finally, the simulation experimental results show that proposed algorithm is effective and efficient for remotes sensing as well as natural images.",

author = "Shilpa Suresh and Devikalyan Das and Shyam Lal",

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Suresh, S, Das, D & Lal, S 2018, A Framework for Quality Enhancement of Multispectral Remote Sensing Images. in 2017 9th International Conference on Advanced Computing, ICoAC 2017., 8441181, 2017 9th International Conference on Advanced Computing, ICoAC 2017, Institute of Electrical and Electronics Engineers Inc., pp. 9-14, 9th International Conference on Advanced Computing, ICoAC 2017, Chennai, India, 14-12-17. https://doi.org/10.1109/ICoAC.2017.8441181

A Framework for Quality Enhancement of Multispectral Remote Sensing Images. / Suresh, Shilpa; Das, Devikalyan; Lal, Shyam.
2017 9th International Conference on Advanced Computing, ICoAC 2017. Institute of Electrical and Electronics Engineers Inc., 2018. p. 9-14 8441181 (2017 9th International Conference on Advanced Computing, ICoAC 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A Framework for Quality Enhancement of Multispectral Remote Sensing Images

AU - Suresh, Shilpa

AU - Das, Devikalyan

AU - Lal, Shyam

PY - 2018/8/20

Y1 - 2018/8/20

N2 - Researches in satellite image enhancement have been particularly confined to two major areas-contrast enhancement and image de noising of remote sensing images. The processing of relatively dark or shadowed images necessitates the need for robust remote sensing enhancement techniques. In this paper, a robust framework for quality enhancement of multispectral remote sensing images is proposed. The quantitative results of proposed algorithm and other existing remote sensing enhancement algorithms are calculated in terms of DE, NIQMC, BIQME, PisDist and CM on different remote sensing and other image databases. Results reveal that visual enhancement of the proposed algorithm is better than other existing remote sensing enhancement algorithms. Finally, the simulation experimental results show that proposed algorithm is effective and efficient for remotes sensing as well as natural images.

AB - Researches in satellite image enhancement have been particularly confined to two major areas-contrast enhancement and image de noising of remote sensing images. The processing of relatively dark or shadowed images necessitates the need for robust remote sensing enhancement techniques. In this paper, a robust framework for quality enhancement of multispectral remote sensing images is proposed. The quantitative results of proposed algorithm and other existing remote sensing enhancement algorithms are calculated in terms of DE, NIQMC, BIQME, PisDist and CM on different remote sensing and other image databases. Results reveal that visual enhancement of the proposed algorithm is better than other existing remote sensing enhancement algorithms. Finally, the simulation experimental results show that proposed algorithm is effective and efficient for remotes sensing as well as natural images.

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Y2 - 14 December 2017 through 16 December 2017

ER -

A Framework for Quality Enhancement of Multispectral Remote Sensing Images

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