Capturing High-resolution Texture Using CAD Data

A System for Capturing High Resolution Images

In this paper an Automatic System for Image Digital Capturing (ASIDC) is described. The aim of ASIDC is to create high resolution digital images depicting paintings of large size. The system creates a set of N digital images presenting sequential frames of the total picture. By using software we proceed to the mosaicing (pasting) of the images producing the complete detailed digital image.

Retrieval using texture features in high-resolution multispectral satellite imagery

Texture features have long been used in remote sensing applications to represent and retrieve image regions similar to a query region. Various representations of texture have been proposed based on the Fourier power spectrum, spatial co-occurrence, wavelets, Gabor filters, etc. These representations vary in their computational complexity and their suitability for representing different region t...

Using high-resolution displays for high-resolution cardiac data.

The ability to perform fast, accurate, high-resolution visualization is fundamental to improving our understanding of anatomical data. As the volumes of data increase from improvements in scanning technology, the methods applied to visualization must evolve. In this paper, we address the interactive display of data from high-resolution magnetic resonance imaging scanning of a rabbit heart and s...

Image Inpainting for High-Resolution Textures using CNN Texture Synthesis

Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) for image inpainting of large regions in high-resolution textures. Due to limited computational resources processing high-resolution images with neural networks is still an open...

Road surface texture inspection using high resolution transverse profile measurements