Subpixel rendering

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

A deep learning semantic template matching framework for remote sensing image registration

Abstract: We propose a deep learning framework by the probability of the predicting semantic spatial position distribution for remote sensing image registration. Traditional matching methods optimize similarity metrics with pixel-by-pixel searching, which is time consuming and sensitive to radiometric differences. Driven by learning-based methods, we take the reference and template images as inputs and map them to the semantic distribution position of the corresponding reference image. We apply the affine invariant to obtain a correspondence between the overlap of the barycenter position of the semantic template and the center pixel point, which transforms the semantic boundary alignment into a point-to-point matching problem. Additionally, two loss functions are proposed, one for optimizing the subpixel matching position and the other for determining the semantic spatial probability distribution of the matching template. In this work, we explore the influence of the template radius size, the filling form of training labels, and the weighted combination of loss function on the matching accuracy. Our experiments show that the trained model is robust to template deformation while still operating orders of magnitude faster. Furthermore, our proposed method implements high matching accuracy in four large scene images with radiometric differences. This ensures the improved speed of remote sensing image analysis and pipeline processing while facilitating novel directions in learning-based registration. Our code is freely available at https://github.com/liliangzhi110/semantictemplatematching .

Multiobjective Subpixel Land-Cover Mapping

Abstract: The hyperspectral subpixel mapping (SPM) technique can generate a land-cover map at the subpixel scale by modeling the relationship between the abundance map and the spatial distribution image of the subpixels. However, this is an inverse ill-posed problem. The most widely used way to resolve the problem is to introduce additional information as a regularization term and acquire the unique optimal solution. However, the regularization parameter either needs to be determined manually or it cannot be determined in a fully adaptive manner. Thus, in this paper, the multiobjective subpixel land-cover mapping (MOSM) framework for hyperspectral remote sensing imagery is proposed, in which the two function terms [the fidelity term and the prior term (i.e., the regularization term)] can be optimized simultaneously, and there is no need to determine the regularization parameter explicitly. In order to achieve this goal, two strategies are designed in MOSM: 1) a high-resolution distribution image-based individual encoding strategy is designed in order to calculate the prior term accurately and 2) a subfitness-based individual comparison strategy is designed in order to generate subpixel land-cover mapping solutions with a high quality to update the population. Four data sets (one simulated, two synthetic, and one real hyperspectral image) were used to test the proposed method. The experimental results show that MOSM can perform better than the other subpixel land-cover mapping methods, demonstrating the effectiveness of MOSM in balancing the fidelity term and prior term in the SPM model.

Polarized light grid stereoscopic display device

Abstract: A three-dimensional display for viewing two-dimensional image and three-dimensional image is provided, which comprises a common two-dimensional image display device (LCD panel, plasma panel and CRT display are all available), a polarized light grid screen and a polariscope, wherein, the polarized light grid screen in the shape of raster comprises two kinds of polarized elements whose polarization orientations are mutually perpendicular lines, which are the first polarized element and the second polarized element. The two polarized elements are overlapped with each other on both horizontal direction and vertical direction. Each polarized element at least corresponds to one subpixel on the display device, which is one of the red subpixel, green subpixel and blue subpixel.

Performance Prediction of Matched Filter and Adaptive Cosine Estimator Hyperspectral Target Detectors

Abstract: Many applications of hyperspectral remote sensing involve the detection of subpixel targets for search and rescue or defense and intelligence operations. The design and potential capabilities of these systems depends on their target detection performance. Therefore, it is important to have tools that reliably predict the performance of target detection systems under different realistic situations. The purpose of this paper is to present a hyperspectral target performance prediction model for the widely used matched filter (MF) and adaptive cosine estimator (ACE) detectors. We use a replacement signal model for resolved and subpixel targets and a finite probability mixture of t-elliptically contoured distributions ( t-ECDs) for the background. A major contribution of this paper is the development of a robust analytical and numerical approach to determine the output distribution of ACE for mixtures of t-ECDs. The proposed technique can be a very useful tool for evaluating target detection performance for highly complex backgrounds.

High-resolution autostereoscopic display and method for displaying three-dimensional images

Abstract: A display device ( 10 ) having pixels elements ( 118 ) divided into subpixel zones ( 131 ), so that each subpixel zone is associated to a predetermined viewing direction ( 160, 162, and 164 ). The light outputs of subpixel zones are controlled by an array of scanning focused electron beams ( 82 ). Each electron beam corresponds to a different pixel. The subpixel zones of the pixel are activated by electron beam in accordance with the input data signal ( 280 ). An array of microlenses ( 120 ) is provided in front of the pixels, so that each column of microlenses corresponds to a different column of pixels. The microlens projects the light outputs of the subpixel zones of the corresponding pixel into observation directions ( 170, 204 ) creating direction-dependent view of the pixel. The thin-panel display device is capable generating high-resolution real-like 3D images of scenes, objects, and models. Observers do not require wearing any special devices or glasses.