In this paper, a model of radar backscattering from rain-generated stalks on the ocean surface in a rain field is proposed. In the model, stalks in the rain field form an array and are considered as finite water cylinders standing out of an infinite water surface. The radar backscattering coefficient from these stalks is derived. Both incoherent and coherent backscattering mechanisms from the stalks are considered. The model shows that the radar backscattering intensity is a function of the average distance between stalks on the water surface, the radar wave frequency, and the incident angle of radar waves. For light/moderate rain (at low rain rates), the radar backscattering intensity increases with increasing rain rate. For heavy rain (at high rain rates), the radar backscattering intensity decreases with increasing rain rate. The maximum radar backscattering intensity occurs at a rain rate that depends on the radar wave frequency and the incident angle of radar waves. The present model is used to explain the radar signatures of a rainfall event simultaneously observed by C-band ENVISAT (European satellite) Advanced Synthetic Aperture Radar (ASAR) and ground-based weather radar in the Northwest Pacific. The relationship between the radar return intensity extracted from the C-band ASAR image and the rain rate obtained from ground-based weather radar is in agreement with the model's calculation. Also, the air-sea interface in rain fields and its effects on the attenuation of radar backscattering are experimentally studied in the laboratory.

Interim results of a laboratory investigation of the low-grazing angle radar backscatter generated by plunging breakers are presented. A primary objective of this investigation is to experimentally verify a scattering mechanism through which the horizontally-polarized backscatter generated by the breaker can exceed that at vertical polarization, without involving multipath propagation between the front face of the wave and its crest. The experiments were conducted at the University of Maryland-College Park wave tank, and involved the deployment of a dual-polarized, ultrawideband radar, multiple high-speed visible cameras, and an ultra-sensitive infrared camera. All instruments were deployed simultaneously on a moving carriage, located above the wave tank channel, that followed the breakers as they evolved in space and time. Representative ultrawideband radar data and optical images are presented in this paper

Radar scattering experiments were carried out at the wavetank facility at the University of Maryland-College Park. Spilling and plunging breakers were generated by means of a chirped wave packet, and were then imaged with a high-speed camera. Simultaneously, the radar backscatter generated by the breakers at a nominal grazing angle of 12 degrees was measured by an ultrawideband, dual-polarized, X-band radar with a range resolution of approximately 4 cm. This experimental setup also included a moving instrument carriage that allowed the sensors to follow the breakers throughout their entire evolution. In conjunction with numerical simulations, these experiments can guide the development of realistic scattering models by identifying the important wave features and the corresponding scattering mechanisms.

Image flow fields from parallel stereo cameras are analyzed to determine the relative 3-D translational motion of the camera platform with respect to objects in view and to establish stereo correspondence of features in the left and right images. A two-step procedure is suggested. In the first step, translational motion parameters are determined from linear equations the coefficients of which consist of the sums of measured quantities in the two images. Separate equations are developed for cases when measurements of either the full optical flow or the normal flow are available. This computation does not require feature-to-feature correspondence. In addition, no assumption is made about the surfaces being viewed. In the second step of the calculation, with the knowledge of the estimated translational motion parameters, the binocular flow information is used to find features in one image that correspond to given features in the other image. Experimental results with synthetic and laboratory images indicate that the method provides accurate results even in the presence of noise.>

A method for the detection of motion in image sequences is presented. In this method, the intensity history at each pixel is convolved with the second derivative in time of a temporal Gaussian smoothing function. The zero crossings in a single frame of the resulting function indicate the positions of moving edges. Intensity changes in time due to illumination effects do not produce zero crossings; thus, they are not interpreted as motion by the present method. It is also shown that the spatial and temporal derivatives of this function can be used to compute the component of the optical flow that is normal to the zero-crossing contours. This computation is also insensitive to nonconvective temporal and spatial variations in the image intensity that are caused by illumination effects.>

A new method for the detection of motion and the computation of optical flow is presented. In the first step of the calculation the intensity history at each pixel is convolved with the second derivative in time of a temporal Gaussian smoothing function. The zero crossings in a single frame of the resulting function indicate the positions of moving edges. Spatial and temporal derivatives of the function at the zero-crossing locations are then used to compute the component of the flow that is normal to the zero-crossing contours. Both the detection of motion and the computation of the normal velocity are insensitive to slow temporal and spatial changes in the image intensity that are caused by illumination effects rather than motion. A framework in which to relate the present work to a number of gradient based flow measurement techniques is also presented.

The analyses of visual data by stereo and motion modules have typically been treated as separate parallel processes which both feed a common viewer-centered 2.5-D sketch of the scene. When acting separately, stereo and motion analyses are subject to certain inherent difficulties; stereo must resolve a combinatorial correspondence problem and is further complicated by the presence of occluding boundaries, motion analysis involves the solution of nonlinear equations and yields a 3-D interpretation specified up to an undetermined scale factor. A new module is described here which unifies stereo and motion analysis in a manner in which each helps to overcome the other's short-comings. One important result is a correlation between relative image flow (i.e., binocular difference flow) and stereo disparity; it points to the importance of the ratio ¿ ¿, rate of change of disparity ¿ to disparity ¿, and its possible role in establishing stereo correspondence. The importance of such ratios was first pointed out by Richards [19]. Our formulation may reflect the human perception channel probed by Regan and Beverley [18].