Topic
Subpixel rendering
About: Subpixel rendering is a research topic. Over the lifetime, 3885 publications have been published within this topic receiving 82789 citations.
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TL;DR: A new approach based on a back-propagation neural network with a HR map (BPNN_HRM), in which a supervised model is introduced into SLCCD for the first time, outperforms the other traditional methods in providing a more detailed map for change detection.
Abstract: Extracting subpixel land-cover change detection (SLCCD) information is important when multitemporal remotely sensed images with different resolutions are available. The general steps are as follows. First, soft classification is applied to a low-resolution (LR) image to generate the proportion of each class. Second, the proportion differences are produced by the use of another high-resolution (HR) image and used as the input of subpixel mapping. Finally, a subpixel sharpened difference map can be generated. However, the prior HR land-cover map is only used to compare with the enhanced map of LR image for change detection, which leads to a nonideal SLCCD result. In this letter, we present a new approach based on a back-propagation neural network (BPNN) with a HR map (BPNN_HRM), in which a supervised model is introduced into SLCCD for the first time. The known information of the HR land-cover map is adequately employed to train the BPNN, whether it predates or postdates the LR image, so that a subpixel change detection map can be effectively generated. In order to evaluate the performance of the proposed algorithm, it was compared with four state-of-the-art methods. The experimental results confirm that the BPNN_HRM method outperforms the other traditional methods in providing a more detailed map for change detection.
20 citations
Patent•
10 Feb 2017
TL;DR: In this article, a display panel includes an array of subpixels in a first, a second, and a third colors, which are alternatively arranged in every three adjacent rows of the array.
Abstract: An apparatus includes a display panel. In one example, the display panel includes an array of subpixels in a first, a second, and a third colors. Subpixels in the first, second, and third colors are alternatively arranged in every three adjacent rows of the array of subpixels. Every two adjacent rows of the array of subpixels are staggered with each other. A first subpixel in one of the first, second, and third colors and a second subpixel in a same color as the first subpixel are offset by 3 units in the horizontal axis and 4 units in the vertical axis. The first and second subpixels have a minimum distance among subpixels in the same color.
20 citations
TL;DR: This letter applies a phase correlation approach to detect subpixel shifts between B2, B3, and B4 Sentinel-2A/MSI images, and shows that shifts of more than 1.1 pixels can be observed for moving targets, such as airplanes and clouds, and can be used for cloud detection.
Abstract: This letter aims at analyzing subpixel misregistration between multispectral images acquired by the Multi Spectral Instrument (MSI) aboard Sentinel-2A remote sensing satellite, and exploring its potential for moving target and cloud detection. By virtue of its hardware design, MSI’s detectors exhibit a parallax angle that leads to subpixel shifts that are corrected with special preprocessing routines. However, these routines do not correct shifts for moving and/or high-altitude objects. In this letter, we apply a phase correlation approach to detect subpixel shifts between B2 (blue), B3 (green), and B4 (red) Sentinel-2A/MSI images. We show that shifts of more than 1.1 pixels can be observed for moving targets, such as airplanes and clouds, and can be used for cloud detection. We demonstrate that the proposed approach can detect clouds that are not identified in the built-in cloud mask provided within the Sentinel-2A Level-1C product.
20 citations
02 Jun 1998
TL;DR: A new stereo matching algorithm, in which the matching of occluded areas is suppressed by a self-organizing process, which describes by coupled, non-linear evolution equations, the continuity and the uniqueness constraints are established.
Abstract: In this paper we introduce a new stereo matching algorithm, in which the matching of occluded areas is suppressed by a self-organizing process. In the first step the images are filtered by a set of oriented Gabor filters. A complex-valued correlation-based similarity measurement, which is applied to the responses of the Gabor filters, is used in the second step to initialize a self-organizing process. In this self-organizing network, which is described by coupled, non-linear evolution equations, the continuity and the uniqueness constraints are established. Occlusions are detected implicitly without a computationally intensive bidirectional matching strategy. Due to the special similarity measurement, dense disparity maps can be calculated with subpixel accuracy. Unlike phase-difference methods the disparity range is not limited to the modulation wavelength of the quadrature-filter. Therefore, there is no need for a hierachical coarse-to-fine control strategy in our approach.
20 citations
03 Jan 1988
TL;DR: A novel method for curve detection based on the moment-preserving principle that derives a parabolic equation as well as a width value to describe the curve segment can be used to estimate curve locations and widths to subpixel accuracy.
Abstract: A novel method for curve detection based on the moment-preserving principle is proposed. The method can be used to estimate curve locations and widths to subpixel accuracy. For each 4.5-unit circle in an input image that includes a curve segment, the approach derives a parabolic equation as well as a width value to describe the curve segment. Experimental results are included to show the effectiveness of the proposed detector. >
20 citations