Using Nonlinear Image Processing Techniques for Realizing Seismogenic Lineaments in Northern Regions of Iran

ETM based photomaps, which of spectral signatures have been acquired by Landsat7 technologies, may contain a large amount of information critical for realizing seismogenic lineaments. False color composite of spaceborne images however are not ready to use dataset for determining lineaments as the main fabrics related to hazardous regions only if the different quantities of the digital numbers have been clearly analyzed by professional statistics. As a rule, current seismic resources have some physical effects straight on the crustal dynamical formation may be occurred by oriented strains along seismic fault systems. In this research, fractal filtering techniques have been used to realize the coherent signatures of remotely sensed structures by means of nonlinear relationships. Magnitude - Area equation and the power-spectra relations are two types of mathematical expressions for analyzing of electromagnetic signatures using multidisciplinary approaches. According to the earthquake catalogues, a few cross cutting structures are playing the main roles for generating seismic potentials in active fault regions. Therefore, nonlinear analysis of those remotely sensed data which contains of the temporal and Fourier transformed quantities, give rise to useful series of self similar spectra for resolving the complexities of the epicenters and adjacent lineaments. Slope-based discrimination between self-similar populations is an essential approaching toward fractal filtering techniques. As a result, several decomposed lineaments with meaningful seismic potentials could be realized by frequency enhancement processes for better understanding of the earthquake patterns in Alamoot Sofla region as a part of the great seismogenic zones in north of Iran