Open AccessLow Complexity Fluctuation Measurement in Image Processing Considering Order
Author(s) -
Tareq Khan
Publication year - 2018
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v8i6.pp4253-4257
Subject(s) - randomness , computer science , measure (data warehouse) , image (mathematics) , pixel , algorithm , entropy (arrow of time) , real number , image processing , set (abstract data type) , order (exchange) , standard deviation , mathematics , artificial intelligence , data mining , discrete mathematics , statistics , physics , finance , quantum mechanics , economics , programming language
The standard deviation can measure the spread out of a set of numbers and entropy can measure the randomness. However, they do not consider the order of the numbers. This can lead to misleading results where the order of the numbers is vital. An image is a set of numbers (i.e. pixel values) that is sensitive to order. In this paper, a low complexity and efficient method for measuring the fluctuation is proposed considering the order of the numbers. The proposed method sums up the changes of consecutive numbers and can be used in image processing applications. Simulation shows that the proposed method is 8 to 33 times faster than other related works.