Search

Palaeobiogeographical distribution of gastropod genera from the Paleocene and the Eocene has been analysed. Based on this distribution, formal palaeobiogeographical provinces have been established and their relationships are sought. It has been found that the provinces were largely restricted to the palaeo-tropics and subtropics mainly of the northern hemisphere and they share a large proportion of their generic composition. The Northern Tropical Realm has been established to include these provinces. The distribution evinces presence of ocean surface currents in the tropics across longitudes. The possible currents moved through the relict Tethys Ocean, across the Atlantic Ocean and perhaps also across the Pacific. However, planktotrophic larvae of these benthic molluscs could not cross the deep ocean barrier that lay between the Northern Tropical Realm and the Austro-New Zealand Province of the southern hemisphere. The gastropod fauna in the latter province evolved independently. Distribution of all the provinces within palaeo-tropics and subtropics indicates strong control of temperature over it. Paleocene–Eocene Thermal Maximum appears to be responsible for extinction and range contraction of high latitude faunas. Low latitude faunas also suffered significant extinction. However, large diversification in the Eocene was a response to widespread transgression that coincided with the thermal event.

The cerithioids are a diverse group of gastropods found globally as fossil and living animals during the Cenozoic Era. Their systematics is riddled with problems stemming from large morphological variability, homoplasy, and wide geographical distribution. Six cerithioid species are described here from the lower Middle Eocene of Kutch, Gujarat, western India. All but two are new species. They are Palmerella kutchensis, Tenagodus? sowerbyi, Potamides archiaci, and Cerithium harudiensis. The rest are new records from Kutch and were known only from Pakistan. A palaeobiogeographical review based on major published records of benthic molluscs from Pakistan reveals strong endemism. The cerithioid faunas from different parts of Pakistan and this report from Kutch also show strong endemism and often quite localized development. It is argued here that unhindered faunal mixing was not possible in this province since these newly evolved basins were restricted in nature in their Lower Cenozoic history.

A new algorithm for the turbulence degraded frames of an underwater object or scene to produce images with superior quality and higher resolution is presented. This approach is based on computing the centroid image of the sequence through an iterative scheme. A robust and fast optical flow technique is employed for pixel registration of all the frames against a reference frame and the pixel shift maps are determined. Using these shift maps, each distorted frame is restored through an image dewarping technique. A performance comparison between the proposed restoration approach and state-of-the-art is presented in terms of restoration time and accuracy. The effectiveness of the approach is demonstrated on both synthetic and real-world underwater videos.

The subfamily Eucycloceratinae Spath, 1928, belonging to the family Sphaeroceratidae, is an important Indo-Madagascan faunal element and is reported here from the Callovian of Kutch, India. Previously the subfamily was considered to consist of 14 morphospecies placed in four morphogenera. The present study is based on re-examination of the type material and more than 350 new specimens, collected with secure stratigraphical control, from sections in mainland Kutch. It reveals that the subfamily includes only two highly variable monospecific genera: Eucycloceras Spath, 1924 and Idiocycloceras Spath, 1928. Dimorphism in Eucycloceratinae, which was not previously recognized, is firmly established. Cladograms have been constructed, based on numerous morphological characters, which show relationships among different subfamilies of the Sphaeroceratidae and genera of the Macrocephalitinae and Eucycloceratinae. The palaeobiogeography and evolution of the Eucycloceratinae are discussed in the light of the new data.

Long-distance surveillance is a challenging task because of atmospheric turbulence that causes time-varying image shifts and blurs in images. These distortions become more significant as the imaging distance increases. This paper presents a new method for compensating image shifting in a video sequence while keeping real moving objects in the video unharmed. In this approach, firstly, a highly accurate and fast optical flow technique is applied to estimate the motion vector maps of the input frames and a centroid algorithm is employed to generate a geometrically correct frame in which there is no moving object. The second step involves applying an algorithm for detecting real moving objects in the video sequence and then restoring it with those objects unaffected. The performance of the proposed method is verified by comparing it with that of a state-of-the-art approach. Simulation experiments using both synthetic and real-life surveillance videos demonstrate that this method significantly improves the accuracy of image restoration while preserving moving objects.

This paper presents the application of artificial neural network for predicting the warping of images of remote objects or scenes ahead of time. The algorithm is based on estimating the pattern of warping of previously captured short-exposure frames through a generalized regression neural network (GRNN) and then predicting the warping of the upcoming frame. A high-accuracy optical flow technique is employed to estimate the dense motion fields of the captured frames, which are considered as training data for the GRNN. The proposed approach is independent of the pixel-oscillatory model unlike the state-of-the-art Kalman filter (KF) approach. Simulation experiments on synthetic and real-world turbulence degraded videos show that the proposed GRNN-based approach performs better than the KF approach in atmospheric warp prediction.

A high accuracy image dewarping method is proposed to restore images from non-uniformly warped video sequences degraded by atmospheric turbulence. This approach contains three major steps. First, a non-rigid image registration technique is employed to register all the frames in the sequence to a reference frame and estimate the motion fields. Second, an iterative First Register Then Average And Subtract (iFRTAAS) method is applied to correct the geometric deformations of the warped frames. The third step involves applying a non-local means filter for the compensation of noise and to improve the signal-to-noise ratio (SNR) of the restored reference frame. Simulations are carried out by applying the method to synthetic and real-life turbulence degraded videos and by determining various quality metrics. A performance comparison is presented between the proposed method and two earlier methods, which verifies that the proposed method provides significant improvement on the image restoration accuracy.