Image interpolation is used in many areas of image processing. It seen that techniques developed to date have been successful both protecting edges and increasing quality. However, these generally detect with gradient-based linear calculations. In this study, spiking neural networks (SNNs), which are known successfully simulate the human visual system (HVS), edge pixels instead gradient. With h...

Numerical lagrangian analysis of the Chesapeake Bay can reveal dynamical features not obtainable through analytical means. These features can indicate coherent structures within the Bay, revealing neighboring regions of fluid that have very different behaviors. Given the model-based discrete velocity data of the bay, obtained through the use of the Regional Ocean Modeling System (ROMS), we impl...

In order to overcome the influence of background, lighting, deformation, and other factors, using a constitutional neural network structure combined with metric learning, specifically, it includes two model structures, Siamese, Triplet. The use bicubic NURBS surfaces is proposed, idea constructing mannequins garment pieces, experimental results show that surface control flexible simple, calcula...

Image up-sampling is found to be a very effective technique useful in today’s digital image processing applications or rendering devices. In image upsampling, an image is enhanced from a lower resolution to a higher resolution with the degree of enhancement depending upon application requirements. It is known that the traditional interpolation based approaches for up-sampling, such as Bilinear ...

Green functions of the biharmonic operator, in one and two dimensions, are used for minimum curvature interpolation of irregularly spaced data points. The interpolating curve (or surface) is a linear combination of Green functions centered at each data point. The amplitudes of the Green functions are found by solving a linear system of equations. In one (or two) dimensions this technique is equ...

This paper focuses on the representation and view generation of three-dimensional (3-D) scenes. In contrast to existing methods that construct a full 3-D model or those that exploit geometric invariants, our representation consists of dense depth maps at several preselected viewpoints from an image sequence. Furthermore, instead of using multiple calibrated stationary cameras or range scanners,...

The semi-Lagrangian method is used for advection experiments on an irregular grid. A cosine hill is advected using a speci ed ow eld corresponding to solid body rotation. A major di culty is to nd an interpolator which is at least fourth order accurate on an unstructured mesh. Such accuracy is needed for the treatment of Rossby waves in ocean models. We develop such a method using a dual krigin...

This paper introduces a wire-frame method for the generation of blending surfaces. It is a numerical approach to the design of surfaces that smoothly join two or more given surfaces. The blending surface generated by the wire-frame method is composed of a set of bicubic patches in parametric forms. The wire-frame method first constructs a set of wire-frames. Each element of the wire-frame is mo...

1 In our CVPR 2016 paper [1], we proposed a novel network architecture to perform single image super­resolution (SR). Most existing convolutional neural network (CNN) based super­resolution methods [10,11] first upsample the image using a bicubic interpolation, then apply a convolutional network. We will refer to these types of networks as high­resolution (HR) networks because the images are up...