Noise reduction in synthetic aperture radar images using fuzzy logic and genetic algorithm

Synthetic aperture radar (SAR) is a self-illuminating imaging technique; it produces high resolution images in all weather conditions, day and night. SAR images are widely accepted and used by many application scientists. However, the SAR images are corrupted with speckle noise. Speckle noises are caused by random interference of electromagnetic signals scattered by the object surface within one resolution element. The amount of noise and distribution of noise corrupting the image is unpredictable. Conventional noise filters are quantitative in nature; they are not well suited for uncertainty problems. Fuzzy logic is capable of handling uncertainty. In this work, noisy pixels in the images are identified by using fuzzy rules and filtered using fuzzy weighted mean, keeping the healthy pixels unchanged. The optimum value of parameters used in defining fuzzy membership function is determined by using genetic algorithm (GA). Reducing noise and simultaneously preserving image details are the two most desirable characteristics of noise filters. Peak signal-to-noise ratio (PSNR) and edge preserving factor (EPF) are used to evaluate the performance of the proposed fuzzy filter. SAR images affected by varying amounts of speckle noise are used to evaluate the performance. It was observed that the proposed filter suppresses noise and preserves image edges.

     

Habitat suitability modeling of a conservation-significant fish species of the Kosi River,Uttarakhand, India

Water quality plays a vital role in the sustenance of aquatic life, including fish. Therefore, an inclusive understanding of water quality parameters can be considered an essential step in framing the conservation and management strategy of an aquatic ecosystem. This study examines the habitat suitability of a conservation-significant fish, the Tor putitora, and two associated fishes, the Labeo dyocheilus and the Garra gotyla, in relation to the water quality parameters of the Kosi River. Four crucial water quality parameters, water temperature, dissolved oxygen, electrical conductivity, and pH, were included in the QUAL2K modeling. Furthermore, hydrological processes were modeled using the soil and water assessment tool, and flow was used as an input in the QUAL2K model. The simulated water quality was correlated with fish habitat and analyzed through the analytical hierarchical process (AHP). Results suggested that the habitats of the Kosi were more suitable in the post-monsoon rather than pre-monsoon. Tor putitora, the flagship species of the Kosi, preferred the river habitats with a lower water temperature and higher dissolved oxygen for spawning. Thus, we recommend securing such habitats and managing them in collaboration with local communities for the long-term conservation of this endangered Himalayan species.     

Vermitechnology for sewage sludge recycling

The present paper is aimed at safe reuse and recycling of sewage sludge (SS) and production of good quality compost using vermicomposting. Three different earthworm species Eiseniafetida (E. fetida), Eudrilus eugeniae (E. eugeniae), Perionyx excavatus (P. excavatus) in individual and combinations were utilized to compare the suitability of worm species for composting of sewage sludge as well as the quality of the end product. The sewage sludge without blending can be directly converted into good quality fertilizer (vermicompost). Vermicomposting resulted in reduction in C/N ratio 25.6 to 6-9, TOC (25%) but increase in electrical conductivity (EC) (47-51%), total nitrogen (TN) (2.4-2.8 times), potassium (45-71%), calcium (49-62%), sodium (62-82%) and total phosphorous (TP) (1.5-1.8 times), which indicated that sewage sludge can be recycled as a good quality fertilizer. The present study also inferred that the application of sewage sludge in the agricultural fields after vermicomposting would not have any adverse effect as the heavy metals (Cu, Mn, Pb and Zn) are now within the permissible limits.