Improved image visualisation through statistical techniques

Author

Vadakkoot, Raveendran ; Raghavendra, Achuth

Author_Institution

Infosys, PIE, Bangalore

fYear

2009

fDate

25-27 May 2009

Firstpage

2405

Lastpage

2407

Abstract

Moving Average is a known technique used in the analysis of time-series data. Quite commonly it is used as a technique to smooth out spikes and highlight the trends. However when carefully applied to image data, moving average can produce quite effective results and with considerable improvement to computational performance. The topic discussed here uses an 8 point moving average computation algorithm. The algorithm used here applies like a low pass filter, taking on the spikes in the image data into consideration and eases out the effect of the noise if any.

Keywords

data analysis; data visualisation; image processing; low-pass filters; moving average processes; smoothing methods; statistical analysis; time series; image processing; image spike smoothing technique; image visualisation; low pass filter; moving average computation algorithm; statistical technique; time-series data analysis; Data analysis; Data visualization; Image analysis; Image processing; Low pass filters; Noise figure; Pixel; Scattering; Signal processing algorithms; Time series analysis; image processing; low pass filter; moving average;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics and Applications, 2009. ICIEA 2009. 4th IEEE Conference on

Conference_Location

Xi´an

Print_ISBN

978-1-4244-2799-4

Electronic_ISBN

978-1-4244-2800-7

Type

conf

DOI

10.1109/ICIEA.2009.5138631

Filename

5138631