Showing papers on "Subpixel rendering published in 1981"
TL;DR: In this paper, surface radiant temperature fields of subpixel spatial resolution from satellites which contain more than one channel in the thermal infrared spectral region are measured in terms of contributions from two temperature fields, each occupying a portion of the pixel, where the portions are not necessarily contiguous.
654 citations
Proceedings Article•
24 Aug 1981TL;DR: This work has shown thatateral inhibition processing of an image yields subpixel precision in the location of intensity discontinuity edges in a digitized image.
Abstract: Lateral inhibition processing of an image yields subpixel precision in the location of intensity discontinuity edges in a digitized image. The method is illustrated using a 512 × 512 × 8 bit image.
17 citations
07 Dec 1981
TL;DR: Overall, it is found that the simple centroid algorithm provides the optimum performance, giving %1/10 pixel accuracy for S/N=10 and no deadspace, and performance improves for the centroid algorithms and degrades for the least squares fit algorithm as the blur spot size increases.
Abstract: The ability to achieve subpixel peak location accuracy for point source taraets in the cross-scan direction for scanning sensors and in both directions for staring sensors is examined systematically by means of Monte Carlo experiments. The performance of three peak location algorithms (simple centroid, extended centroid, polynomial least squares fit) is tested for sensitivity to system signal-to-noise ratio, detector deadspace, and blur spot size relative to detector size. A symmetrical, gaussian intensity profile of the blur spot is used in all cases. Computational efficiency, in terms of the number of multiplies and adds required, was considered in selecting the algorithms to be compared. Overall, we found that the simple centroid algorithm provides the optimum performance, giving %1/10 pixel accuracy for S/N=10 and no deadspace. In addition, performance improves for the centroid algorithms and degrades for the least squares fit algorithm as the blur spot size increases. Increasing deadspace markedly degrades the performance of the centroid algo-rithms.
15 citations
01 Jan 1981
TL;DR: In this article, the purpose of the considered system is to take pieces of imagery, called control point chips (CPC), whose geodetic location has been previously determined and stored, and locate their position in later imagery of the same area.
Abstract: It is the purpose of the considered system to take pieces of imagery, called control point chips (CPC), whose geodetic location has been previously determined and stored, and locate their position in later imagery of the same area. The registration processes are carried out partially on a DEC VAX 780 computer and partially on a Floating Point Systems Array Processor. Typically sets of 20 control points are processed at a time. To process these as sets, and to optimize the use of both machines, operations are grouped into loops instead of a sequential processing for each point. Attention is given to cloud cover assessment, enhancement, correlation techniques, pixel registration, and subpixel registration.
1 citations