Scale Space Reduction with Interpolation to Speed up Visual Saliency Detection
Author(s) -
Omprakash Rajankar,
Uttam D. Kolekar
Publication year - 2015
Publication title -
international journal of image graphics and signal processing
Language(s) - English
Resource type - Journals
eISSN - 2074-9082
pISSN - 2074-9074
DOI - 10.5815/ijigsp.2015.08.07
Subject(s) - computer science , artificial intelligence , scale space , reduction (mathematics) , kadir–brady saliency detector , scale (ratio) , interpolation (computer graphics) , computer vision , salient , object detection , a priori and a posteriori , pattern recognition (psychology) , image (mathematics) , fast fourier transform , saliency map , object (grammar) , image processing , algorithm , mathematics , geometry , philosophy , physics , epistemology , quantum mechanics
The scale of salient object in an image is not a known priori, therefore to detect salient objects accurately multiple scale analysis is used by saliency detection models. However, multiple scale analysis makes the saliency detection slow. Fast and accurate saliency detection is essential to obtain Region of Interest in image processing applications. This paper proposes a scale space reduction with interpolation to speed up the saliency detection. To demonstrate the concept, this method is integrated with Hypercomplex Fourier Transform saliency detection which reduced the computational complexity from O(N) to O(N/2).
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