The correlation study of parallel feature extractor and noise reduction approaches

Deshinta Arrova Dewi, Elankovan A Sundararajan, Anton Satria Prabuwono

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents literature reviews that show variety of techniques to develop parallel feature extractor and finding its correlation with noise reduction approaches for low light intensity images. Low light intensity images are normally displayed as darker images and low contrast. Without proper handling techniques, those images regularly become evidences of misperception of objects and textures, the incapability to section them. The visual illusions regularly clues to disorientation, user fatigue, poor detection and classification performance of humans and computer algorithms. Noise reduction approaches (NR) therefore is an essential step for other image processing steps such as edge detection, image segmentation, image compression, etc. Parallel Feature Extractor (PFE) meant to capture visual contents of images involves partitioning images into segments, detecting image overlaps if any, and controlling distributed and redistributed segments to extract the features. Working on low light intensity images make the PFE face challenges and closely depend on the quality of its pre-processing steps. Some papers have suggested many well established NR as well as PFE strategies however only few resources have suggested or mentioned the correlation between them. This paper reviews best approaches of the NR and the PFE with detailed explanation on the suggested correlation. This finding may suggest relevant strategies of the PFE development. With the help of knowledge based reasoning, computational approaches and algorithms, we present the correlation study between the NR and the PFE that can be useful for the development and enhancement of other existing PFE.

Original languageEnglish
Title of host publicationInternational Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014
PublisherAmerican Institute of Physics Inc.
Volume1660
ISBN (Electronic)9780735413047
DOIs
Publication statusPublished - 15 May 2015
EventInternational Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014 - Penang, Malaysia
Duration: 28 May 201430 May 2014

Other

OtherInternational Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014
CountryMalaysia
CityPenang
Period28/5/1430/5/14

Fingerprint

noise reduction
luminous intensity
disorientation
illusions
edge detection
preprocessing
image processing
resources
textures
augmentation

Keywords

  • image noise reduction
  • Image processing system
  • knowledge based reasoning
  • parallel feature extraction

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Dewi, D. A., A Sundararajan, E., & Prabuwono, A. S. (2015). The correlation study of parallel feature extractor and noise reduction approaches. In International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014 (Vol. 1660). [090001] American Institute of Physics Inc.. https://doi.org/10.1063/1.4915845

The correlation study of parallel feature extractor and noise reduction approaches. / Dewi, Deshinta Arrova; A Sundararajan, Elankovan; Prabuwono, Anton Satria.

International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014. Vol. 1660 American Institute of Physics Inc., 2015. 090001.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Dewi, DA, A Sundararajan, E & Prabuwono, AS 2015, The correlation study of parallel feature extractor and noise reduction approaches. in International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014. vol. 1660, 090001, American Institute of Physics Inc., International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014, Penang, Malaysia, 28/5/14. https://doi.org/10.1063/1.4915845
Dewi DA, A Sundararajan E, Prabuwono AS. The correlation study of parallel feature extractor and noise reduction approaches. In International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014. Vol. 1660. American Institute of Physics Inc. 2015. 090001 https://doi.org/10.1063/1.4915845
Dewi, Deshinta Arrova ; A Sundararajan, Elankovan ; Prabuwono, Anton Satria. / The correlation study of parallel feature extractor and noise reduction approaches. International Conference on Mathematics, Engineering and Industrial Applications, ICoMEIA 2014. Vol. 1660 American Institute of Physics Inc., 2015.
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