Subpixel rendering

About: Subpixel rendering is a research topic. Over the lifetime, 3885 publications have been published within this topic receiving 82789 citations.

System and method for rapid shape digitizing and adaptive mesh generation

Abstract: System and method for rapid collection of data points and construction of a computer model based on a multi-resolution mesh to describe the surface contours and color of an object (101). The system collects data by projecting shapes of light (121-125) against the object (101) and collecting (from a position of triangulation relative to the light projector) images of the light as it reflects from the object. The system and method are comprised of a multiple laser stripe generation process to project a number of light shapes against the object, the collection of one or more reflected laser stripes in a single image of an images collector (120) to gather sufficient information to reproduce points on the surface of the object. The system compresses the data associated with collected points, which allows for accurate values for the contours of the object to subpixel accuracy. A multi-resolution analysis, which maintains more points to resolve fine details and removes points to further smooth regions of the objects, leads to significant compression. The adaptive mesh, consisting of the connection of polygonal finite elements, is automatically generated by the system and is comprised to create multi-resolution meshes at different tolerances.

Hyperspectral Remote Sensing Image Subpixel Target Detection Based on Supervised Metric Learning

Abstract: The detection and identification of target pixels such as certain minerals and man-made objects from hyperspectral remote sensing images is of great interest for both civilian and military applications. However, due to the restriction in the spatial resolution of most airborne or satellite hyperspectral sensors, the targets often appear as subpixels in the hyperspectral image (HSI). The observed spectral feature of the desired target pixel (positive sample) is therefore a mixed signature of the reference target spectrum and the background pixels spectra (negative samples), which belong to various land cover classes. In this paper, we propose a novel supervised metric learning (SML) algorithm, which can effectively learn a distance metric for hyperspectral target detection, by which target pixels are easily detected in positive space while the background pixels are pushed into negative space as far as possible. The proposed SML algorithm first maximizes the distance between the positive and negative samples by an objective function of the supervised distance maximization. Then, by considering the variety of the background spectral features, we put a similarity propagation constraint into the SML to simultaneously link the target pixels with positive samples, as well as the background pixels with negative samples, which helps to reject false alarms in the target detection. Finally, a manifold smoothness regularization is imposed on the positive samples to preserve their local geometry in the obtained metric. Based on the public data sets of mineral detection in an Airborne Visible/Infrared Imaging Spectrometer image and fabric and vehicle detection in a Hyperspectral Mapper image, quantitative comparisons of several HSI target detection methods, as well as some state-of-the-art metric learning algorithms, were performed. All the experimental results demonstrate the effectiveness of the proposed SML algorithm for hyperspectral target detection.

Pixel interpolation filters for video decompression processor

Abstract: A method and apparatus are disclosed for interpolating pixels to obtain subpels for use by a video decompression processor. A prediction area is defined from which subpels are necessary to decompress a portion of a video image. Instead of reading all of the pixels from the prediction area and then processing them together to perform the necessary interpolation, portions of the pixel data are read and simultaneously averaged using in-place computation in order to reduce hardware requirements. Rounding of subpixel results is achieved using the carry input of conventional adders to add a binary "1" to the averaged pixels, which are subsequently truncated to provide the interpolated subpels.

Drive circuitry for four-color organic light-emitting device

Abstract: A four-color organic light-emitting device having pixels which emit light includes a substrate; pixels arranged in rows and columns and each pixel including groups of four subpixels disposed over the substrate and wherein each subpixel includes spaced apart first and second electrodes; and organic EL media disposed between the first and second electrodes of each subpixel. The device also includes drive circuitry disposed relative to the organic EL media over the substrate and arranged to drive each group of four subpixels and having an electrical connection to the first electrode corresponding to each subpixel, and wherein the drive circuitry for each group of four subpixels including four data lines, two power lines, and one select line, the four data lines being shared for each column of the array of pixels, and the select line being shared for each row of the array of pixels.