Classification of radar echoes with a textural–fuzzy approach: an application for the removal of ground clutter observed in Sétif (Algeria) and Bordeaux (France) sites

Adaptive Neuro-Fuzzy Inference System for Echoes Classification in Radar Images

“…In this paper, we will use only two parameters (i.e. Local homogeneity and Energy) that give the results the most uncorrelated, with the direction θ =0° and the distance d=1, which correspond to the Cartesian coordinates (Δx=0, Δy=1) (Sadouki and Haddad, 2013).…”

“…For each 5×5 pixels window in a given subimage, we calculated the statistical parameters Energy and Local homogeneity that have been found to be useful in discriminating between precipitations and clutter, and have been chosen as inputs of our classifier. (Sadouki and Haddad, 2013) As result to the previous process, we were capable to construct our database of 1000 vectors that corresponds to our two classes, 500 for clutter and 500 for precipitations. Each vector is composed of 3 elements, Energy, Local homogeneity and class.…”

“…Others applied the fuzzy logic technique, to classify the Doppler radar echoes types (Hubbert et al, 2009) or for identifying non-precipitating echoes in radar scans (Berenguer et al, 2006;Cho et al, 2006). In (Sadouki and Haddad, 2013), they combined the textural properties of the echoes with the fuzzy approach in order de classify the echoes. Furthermore, (Xiang, 2010) used the neuro-fuzzy approach to eliminate noise in Doppler radar signals.…”

“…Depending on the on above literature survey, it's interesting to implement an algorithm which combines the textural features, based on the method of grey-level co-occurrence matrices, and an Adaptive Neuro-Fuzzy System (ANFIS) with grid partition. The input variables for our system are two textural parameters considered as effective elements for distinguishing between precipitation echoes and clutter (Sadouki and Haddad, 2013). This method was applied to the images taken in the region of Sétif (Algeria).…”

Classification of Radar Echoes for Identification and Remote Reading of Chipless Millimeter-Wave Sensors

“…Classification of radar echoes is usually applied to meteorological radar imagery, synthetic aperture radar (SAR) imaging or through-the-wall radar imaging (TWRI). For SAR imaging or meteorological radar images, textural and polarimetric features can be analyzed for segmentation and classification purposes [12] [13], while on TWRI application, classifications can be applied to 3D radar images [14]. Segmentation and identification of 3D radar targets are also possible, as shown in [15].…”