Y. S. Rao

Selection of Suitable Window Size for Speckle Reduction and Deblurring using SOFM in Polarimetric SAR Images

Classification performance of PolSAR data, when used without speckle reduction is insufficient for most applications. Thus, speckle filtering becomes an essential preprocessing step. In this study we evaluate the effectiveness of different popular speckle filters and analyse their effects on the classification accuracy. We have used L-band and C-band fully polarimetric dataset acquired over Mumbai, India. The Wishart supervised classifier algorithm is used for classification of the filtered and unfiltered data. Boxcar, Refined Lee, Lopez, IDAN, Improved Sigma and sequential filters are analysed for the improvement in classification accuracy. Further we also evaluate the effect of window size on classification accuracy in order to be able to select appropriate window for speckle suppression. Boxcar and Refined Lee filters are used to test the effect of speckle filtering on classification with varying moving window size. Boxcar filter is widely used in the SAR application domain owing to it’s simplicity. However, the indiscriminate averaging of the Boxcar filter causes a resolution loss in the vicinity of sharp edges and point targets in the image. To overcome this, we have applied Kohonens Self-Organizing Feature Map (SOFM) algorithm to deblurr the image and improve edge and target preservation performance.

Local Contrast Based Adaptive SAR Speckle Filter

In this paper, we propose an adaptive filtering technique for Synthetic Aperture Radar (SAR) images. A new windowing technique is introduced where the total window is divided into five equal sized overlapping sub-windows. The pixel to be filtered is a part of each of these sub-windows. A weighted mean of all sub-windows is computed for the pixel under consideration. The weights are accounted from a measure of heterogeneity calculated for each sub-windows. The filter is able to adapt automatically and adjust the speckle suppression strength based on local statistics. This allows the filter to preserve edges while strongly suppressing speckle over homogeneous areas. The proposed filter was compared with some well known SAR filtering techniques in terms of speckle suppression and edge preservation ability. Several experiments were performed on datasets acquired from both air-borne and space-borne SAR platforms. Some well known indices were used for quantitative comparison with other filters. Among the filters compared, the proposed filter shows good speckle suppression ability while still exhibiting reasonable edge preservation ability.

Evaluation of RISAT-1 compact polarization data for calibration

Synchronous with RISAT-1 and RADARSAT-2 passes, corner reflectors (CR) were mounted for the evaluation of radiometric calibration of RISAT-1 compact polarimetric SAR data. Based on the CRs response on SLC images, RISAT-1 calibration constant, PSLR/ISLR, resolution, channel imbalance and cross-talk were analyzed and compared with that of product specifications. A difference of 0.5 to 1.5 dB is observed between product and estimated calibration constant K. The resolution and PSLR/ISLR are better than the specification of the product. Backscattering coefficient and compact polarimetric parameters of RISAT-1 were compared with RADARSAT-2 simulated compact polarization. The large difference in sigma-0 is observed for water and sand features due to high value of noise-equivalent-sigma-zero of RISAT-1. Similarly, some differences are observed between RISAT-1 estimated compact polarimetric parameters (m, mc, δ, χ, axial ratio, CPR) and that of RADARSAT-2 simulated compact data.

Self-organizing feature map based polarimetric SAR data denoising

Speckle has a nature of multiplicative noise which is difficult to deal as compared to additive noise. It complicates the problem of interpretation of the image segmentation and classification. The primary goal of existing speckle filtering algorithms, which are subjective in nature is to reduce the speckle without loss of information. Various techniques have been proposed to suppress the speckle. In this paper we propose Self-Organizing Feature Map (SOFM) based polarimetric SAR speckle filter. The filter is evaluated using fully polarimetric ALOSPALSAR and Radarsat-2 data imaged over Mumbai, India. Quantitative and qualitative results revels that SOFM based approach is effective in terms of bias and speckle reduction.

Analysis of full and hybrid polarimetric based descriptors for different land features

The objective of this paper study is to understand the land use land cover type information using C-band RADARSAT-2 data in quad pol and simulated hybrid pol mode. A quad-pol RADARSAT-2 image was used to simulate right circular hybrid polarimetric synthetic aperture radar SAR data. The area under rice cultivation shows dominance of double-bounce scattering, while cotton and banana crops shows dominance of surface scattering in the quad as well as hybrid pol mode. The correlation coefficient is also assessed among different full and compact polarimetric descriptors. The overall investigation shows the comparative strength of hybrid polarimetry for target discrimination and scattering mechanism analysis.

Hybrid and dual linear polarimetric RISAT-1 SAR data for classification assessment

This paper compares the classification capability of data acquired in hybrid and dual linear polarization mode over the Chelmsford area, United Kingdom, from RISAT-1 C-band satellite. Support vector machine based supervised classification is used in the study and accuracy is assessed over the validation pixels. The hybrid-pol RH/RV combination shows better classification accuracy over linear pol HH/HV combination by 2.5 %. Overall classification accuracy is increased to 90% over the given area when Stokes parameter are added to the polarization combination.

Spatio-temporal variation of soil moisture and drought monitoring using passive microwave remote sensing

Soil moisture is one of the important variables in hydrological systems. Spatial and temporal dynamics of soil moisture are important for determining complex environmental process. The aim of the study is to assess the trend of soil moisture in India and to monitor agricultural drought in Medak district of Telangana state during the period 2002 to 2014. Spatio-temporal analysis has been performed on yearly basis using AMSR-E (2002-2010) and SMOS (2010-2014) soil moisture data. Soil Moisture Anomaly Percentage Index (SMAPI) is used for performing spatio-temporal analysis. It has been observed that soil moisture trend shows a dynamic pattern across the country and positive correlation with the precipitation data. Soil moisture anomalies are more in North-Western and North-Eastern part India when compared to other parts. Departure of soil moisture from its mean is used for monitoring drought. Agricultural drought monitoring in Medak district shows that the abnormal pattern of dry spell areas during a particular year matches with that of the drought years.

Comparison of TanDEM-X and Cartosat-1 stereo DEMs over different terrains of India

In this paper, the accuracy of TanDEM-X DEMs is evaluated for different terrains of India and is also compared with that of Cartosat-1 optical stereo DEMs. Using accurate GPS points as reference, TanDEM-X DEMs of Mumbai area with flat as well as low hilly terrain, Koyna area with high hilly terrain, rugged Himalayan terrain of Manali and Katerniaghat area with forest cover over flat terrain were evaluated. The results show an RMSE of 3.3 m, 4.9 m, 12.8 m and 8.7 m for the four test areas respectively. Cartosat-1 DEM over these areas give an RMSE of 4.8 m, 7.9 m, 11.4 m and 8.7 m respectively. The height error also shows its dependence on slope. The difference between the DEMs obtained from the two techniques was also calculated for all the test sites in order to compare their accuracies. For all the test sites except Manali, an RMSE <; 4 m with 90% confidence level was observed between the two DEMs. The rugged terrain of Manali area is highly affected due to layover and shadow effect in TanDEM-X DEM and hence showed higher RMSE when compared with Cartosat-1 DEM. As both DEMs have spatial resolution and high accuracy, gaps in the TanDEM-X DEM may be filled with Cartosat-1 DEM.

Polarisation orientation compensation for detection of oriented settlements in PolSAR image

Classification of settlement is one of the most important applications of Polarimetric Synthetic Aperture Radar (POLSAR). This paper suggests an effective technique for classifying the urban area which is not orthogonal to radar line of sight by using Polarization Orientation Compensation (POC). Polarization orientation information combined with the decomposed image, when classified with decision tree classifier, improves the classification accuracy of urban class by 40%.

Temporal analysis of different crops using quad-pol RADARSAT-2 data

The objective of this study is to understand the temporal characteristic of cotton, sugarcane, banana and rice crop using C-band quad pol RADARSAT-2 data. Temporal response of these crops was analyzed using H/A/α and model based Freeman-Durden decomposition. Results of this preliminary study indicate that the (Entropy, anisotropy α and α1) parameters are sensitive to crop growth stages and can be used for crop mapping and monitoring purpose. The three basic scattering mechanisms (surface, volume and double-bounce) and H/A/α parameters obtained from these decompositions found suitable to distinguish between crop types and their temporal sensitivity.