Y. Rezaei; M. R. Mobasheri; M. J. Valadanzouje
Abstract
Estimation of noise present in Hyperspectral images is a way to enhance the quality of the extracted information and to reduce the uncertainties in the results. The simplest method widely used in noise estimation is Shift Difference. This method has two weaknesses; first, it is based upon the assumption ...
Read More
Estimation of noise present in Hyperspectral images is a way to enhance the quality of the extracted information and to reduce the uncertainties in the results. The simplest method widely used in noise estimation is Shift Difference. This method has two weaknesses; first, it is based upon the assumption that the adjacent pixels have the same signal information which is not necessarily valid in hyperspectral data sets; second, in order to calculate the correct values of noise it needs homogeneous regions that is usually being determined by supervision. In this study, a new method in noise estimation (NETAL) is introduced. In this method the satellite images are divided into homogeneous regions using spectral absorption parameters such as location of absorption lines, width and depth of these absorption features for every individual pixels. Then in each region the noise was calculated using regression between adjacent bands and finally the total noise was estimated through accumulation of the calculated noises in each region. The NETAL algorithm was evaluated by using simulated and real hyperspectral data sets. The results show that the noise estimation by NETAL method is faster than Multiple Regression method while the accuracy will remain the same as and even better than the Multiple Regression method.
M. J. Valadan Zouj; Y. Rezaei; F. Vaziri; M.R. Mobasheri
Abstract
A considerable portion of potable water in Iran is supplied by natural glaciers, and then the study and protection of these resources are a necessity. This investigation includes the assessment of glacier parameters such as maximum and minimum altitude, area and perimeter, position of snow line and etc. ...
Read More
A considerable portion of potable water in Iran is supplied by natural glaciers, and then the study and protection of these resources are a necessity. This investigation includes the assessment of glacier parameters such as maximum and minimum altitude, area and perimeter, position of snow line and etc. Since direct measurement of these parameters in the field is time consuming and expensive, therefore, some techniques such as remote sensing seem to be more useful and plausible. In this regards, one can deploy different algorithms for detection of the glacier region as well as calculation of relevant important parameters. To achieve this goal, the resolution of satellite images in spatial, spectral and radiometric aspects should be studied and assessed. In this research, satellite images with different resolutions have been used to study the Alam Chal Glacier. Using different satellite images, the glacier parameters have been identified and studied and the most appropriate images which can provide the necessary precision for this task were identified. Also the potentiality of DEM (Digital Elevation Model) in combination with satellite images in order to obtain the glacier geometric elements such as the topography of cirque, maximum and minimum height, the topography of the district and watershed, has been investigated.
H. Fattahi; M. J. Valadan Zouj; M. R. Mobasheri; M. Dehghani
Abstract
Interferometric Synthetic Aperture Radar (InSAR) technique using phase information has demonstrated its abilities in topographic mapping and measuring surface deformation with the precision of meter and sub-centimeter, respectively in a very high spatial resolution. However, ...
Read More
Interferometric Synthetic Aperture Radar (InSAR) technique using phase information has demonstrated its abilities in topographic mapping and measuring surface deformation with the precision of meter and sub-centimeter, respectively in a very high spatial resolution. However, various limiting factors such as spatial and temporal decorrelation, atmospheric effects and thermal noise of the radar sensor introduce different types of noise into the interferograms, which makes the phase unwrapping too difficult to obtain the accurate results. In this study, an algorithm for noise suppression is presented based on wavelet transform in the complex domain. The high-frequency data due to the phase jumps is not appeared in the complex domain. Therefore, the wavelet coefficients obtained in the complex domain include mostly the noise. The wavelet coefficients of the noisy interferogram are then filtered using the threshold computed from the related wavelet band. In comparison with the other noise reduction methods such as multi-look processing and those based on Fourier transform in small windows, the proposed algorithm can reduce the noise while keeping the spatial resolution without the need for windowing the interferogram. Quantitative and qualitative evaluations of the results obtained by the new method applied on the simulated and real noisy data show high performance of the wavelet transform in noise reduction.
