2 resultados para Microcystin-LR

em Cochin University of Science


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In this thesis, a detailed attempt has been made to understand the general hydrography of the upper 300m of the water column, in the eastern Arabian Sea and the western Bay of Bengal, the two contrasting basins in the northern Indian Ocean, using recently collected data sets of Marine Research-Living Resources (MR-LR) assessment programme, funded by Department of Ocean Development, from various cruises, pertaining to different seasons. Initially it discuss the general hydrography of the west and east coasts of India are covered, in the context of mixed layer processes. The study describes the materials and methods . To compare the hydrography of the AS and BOB, a unique MLD(Mixed Layer Depth) definition for AS and BOB is essential, for which the 275 CTD profiles were used. A comparison has been made among the various MLD criteria with the actual MLD. The monthly evolution of MLD, barrier layer thickness and the role of atmospheric forcing on the dynamics of the mixed layer in the AS and BOB were studied. The general hydrography along the west coast of India is described. The upwelling/downwelling, winter cooling processes, in the context of chemical and biological parameters, are also addressed. Finally the general hydrography of the Bay of Bengal is covered. The most striking feature in the hydrography are the signature of an anticyclonic subtropical gyre during spring intermonsoon and a cold core eddy during winter monsoon. The TTS(Typical Tropical Structure) of the euphotic layer was also investigated.

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Super Resolution problem is an inverse problem and refers to the process of producing a High resolution (HR) image, making use of one or more Low Resolution (LR) observations. It includes up sampling the image, thereby, increasing the maximum spatial frequency and removing degradations that arise during the image capture namely aliasing and blurring. The work presented in this thesis is based on learning based single image super-resolution. In learning based super-resolution algorithms, a training set or database of available HR images are used to construct the HR image of an image captured using a LR camera. In the training set, images are stored as patches or coefficients of feature representations like wavelet transform, DCT, etc. Single frame image super-resolution can be used in applications where database of HR images are available. The advantage of this method is that by skilfully creating a database of suitable training images, one can improve the quality of the super-resolved image. A new super resolution method based on wavelet transform is developed and it is better than conventional wavelet transform based methods and standard interpolation methods. Super-resolution techniques based on skewed anisotropic transform called directionlet transform are developed to convert a low resolution image which is of small size into a high resolution image of large size. Super-resolution algorithm not only increases the size, but also reduces the degradations occurred during the process of capturing image. This method outperforms the standard interpolation methods and the wavelet methods, both visually and in terms of SNR values. Artifacts like aliasing and ringing effects are also eliminated in this method. The super-resolution methods are implemented using, both critically sampled and over sampled directionlets. The conventional directionlet transform is computationally complex. Hence lifting scheme is used for implementation of directionlets. The new single image super-resolution method based on lifting scheme reduces computational complexity and thereby reduces computation time. The quality of the super resolved image depends on the type of wavelet basis used. A study is conducted to find the effect of different wavelets on the single image super-resolution method. Finally this new method implemented on grey images is extended to colour images and noisy images