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Title: The correlation study of parallel feature extractor and noise reduction approaches

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 findingmore » 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.« less
Authors:
; ;  [1]
  1. Industrial Computing Research Group, Centre for Artificial Intelligence Technology, Universiti Kebangsaan Malaysia, 43600 Bangi (Malaysia)
Publication Date:
OSTI Identifier:
22391684
Resource Type:
Journal Article
Resource Relation:
Journal Name: AIP Conference Proceedings; Journal Volume: 1660; Journal Issue: 1; Conference: ICoMEIA 2014: International Conference on Mathematics, Engineering and Industrial Applications 2014, Penang (Malaysia), 28-30 May 2014; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ALGORITHMS; COMPRESSION; COMPUTER CALCULATIONS; CORRELATIONS; FATIGUE; IMAGE PROCESSING; IMAGES; NOISE; PERFORMANCE; VISIBLE RADIATION