From the temporal spectra of vertical wind obtained from MST radar observations, the Brunt‐Vaisala frequency is identified. Altitude profile of temperature in troposphere and lower stratosphere is derived from the altitude profile of the Brunt‐Vaisala frequency thus obtained.
The paper proposes an improved fast and efficient decision-based algorithm for the restoration of images that are highly corrupted by Salt-and-Pepper noise. The new algorithm utilizes previously processed neighboring pixel values to get better image quality than the one utilizing only the just previously processed pixel value. The proposed algorithm is faster and also produces better result than a Standard Median Filter (SMF), Adaptive Median Filters (AMF), Cascade and Recursive non-linear filters. The proposed method removes only the noisy pixel either by the median value or by the mean of the previously processed neighboring pixel values. Different images have been tested by using the proposed algorithm (PA) and found to produce better PSNR and SSIM values.
Automatic animal sound classification and retrieval is very helpful for bioacoustic and audio retrieval applications. In this paper we propose a system to define and extract a set of acoustic features from all archived wild animal sound recordings that is used in subsequent feature selection, classification and retrieval tasks. The database consisted of sounds of six wild animals. The Fractal Dimension analysis based segmentation was selected due to its ability to select the right portion of signal for extracting the features. The feature vectors of the proposed algorithm consist of spectral, temporal and perceptual features of the animal vocalizations. The minimal Redundancy, Maximal Relevance (mRMR) feature selection analysis was exploited to increase the classification accuracy at a compact set of features. These features were used as the inputs of two neural networks, the k-Nearest Neighbor (kNN), the Multi-Layer Perceptron (MLP) and its fusion. The proposed system provides quite robust approach for classification and retrieval purposes, especially for the wild animal sounds.
Fractal concepts are used to describe the irregular structures and regions of interest of solar images. The most common and easiest way to extract regions of interest from an image is through segmentation. Segmentation techniques vary from conventional edge-detection mechanism to fuzzy c-means clustering. In this study, the pixelwise local fractal dimension of solar images is computed by different techniques. This is followed by different segmentation procedures including the fuzzy-based approach, for extracting the active regions from chromospheric images and assessing their performance. These techniques have also been applied on solar images to extract active regions from Solar Heliospheric Observatory (SOHO) Extreme Ultraviolet Telescope (EIT) images.
Abstract. Fractal geometry is becoming increasingly important in the study of image characteristics. For recognition of regions and objects in natural scenes, there is always a need for features that are invariant and they provide a good set of descriptive values for the region. There are many fractal features that can be generated from an image. In this paper, fractal signatures of nearby galaxies are studied with the aim of classifying them. The fractal signature over a range of scales proved to be an efficient feature set with good discriminating power. Classifiers were designed using nearest neighbour method and neural network technique. Using the nearest distance approach, classification rate was found to be 92%. By the neural network method it has been found to increase to 95%.
Abstract. The vertical velocity in the troposphere-lower stratosphere region measured using MST radar has been utilized to evaluate the temperature profile in the region. The diurnal variation of the tropospheric temperature on one day in August 1998 at the tropical station Gadanki (13.5 • N, 79.2 • E) has been studied using the MST radar technique. The diurnal variation of the temperature revealed a prominent diurnal variation with the peak in the afternoon hours increasingly delayed in altitude. The tropopause temperature and altitude exhibited a clear diurnal cycle.
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