Subpixel rendering

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

Image Registration Using Blur-Invariant Phase Correlation

Abstract: In this paper, we propose an image registration method, which is invariant to centrally symmetric blur The method utilizes the phase of the images and has its roots on phase correlation (PC) registration We show how the even powers of the normalized Fourier transform of an image are invariant to centrally symmetric blur, such as motion or out-of-focus blur We then use these results to propose blur-invariant phase correlation The method has been compared to PC registration with excellent results With a subpixel extension of PC registration, the method achieves subpixel accuracy for even heavily blurred images

Cross correlation image sensor alignment system

Abstract: A system which uses a random noise test target 16 to align sensors 10 and 12 by performing mathematical cross correlations between sensors 10 and 12. The system 48 includes a computer 58 rotating one of the images, computing a correlation between the rotated image and a reference image and determining the peak in the correlation. A global maximum is used to interpolate a true subpixel peak. The interpolated rotational cross correlation peak is used to determine values of two dimensional and rotational movement of one of the sensors 10 and 12 necessary to align the sensors. The values are used to move the sensor 10 or 12 and it is fixed in place. Once the sensors have been aligned and fixed in place, the system 118 computes the cross correlation of segments of the image to determine delay values and an interpolation filter coefficient values which are stored in a permanent storage device 120. The coefficients are used by an correction circuit 122 to correct for regional or spatially varying alignment errors during real time image processing by the imaging system.

Mapping impervious surface area using high resolution imagery: a comparison of object-based and per pixel classification

Abstract: Impervious surface area is a key indicator of environmental quality. Satellite remote sensing of impervious surface has focused on subpixel analysis via various forms of statistical estimation, subpixel classification, and spectral mixture analysis, using medium resolution Landsat TM or ETM+ data. Maps of impervious surface area from these studies provide useful inputs to planning and management activities at city to regional scales. However, for local studies, large-scale, higher resolution maps are preferred. This study investigates digital classification techniques of mapping of impervious surface area using high resolution Quickbird satellite data. Two methods – object-based and per pixel classification – are explored and compared. The results provide information for accurate impervious surface mapping and estimation in high resolution imagery.

Image projection apparatus for producing an image supplied by parallel transmitted colored light

Abstract: A projection apparatus provides a projection engine that supplies polarized light to a dielectric filter (or diffraction grating) The dielectric filter provides an array of pixels that each pass selected colors of light and reflect other colors Each pixel is subpixelated (for example, red, green, and blue subpixels) so that a single subpixel passes a selected color (for example, red) and reflects the other colors (for example, green and blue) A digital micromirror device has an array of mirrors that correspond in number to the number of subpixels of the dielectric filter Each of the mirrors provide "on" and "off" positions for selectively transmitting a desired color of light from the mirror to an image screen The image screen receives light reflected by selected of the mirrors of the array of micromirrors when the selected mirrors are in the "on" position The micromirror device can be controlled with a computer, television, signal, video signal, or the like

An Approach for Subpixel Anomaly Detection in Hyperspectral Images

Abstract: Fast detecting difficult targets such as subpixel objects is a fundamental challenge for anomaly detection (AD) in hyperspectral images. In an attempt to solve this problem, this paper presents a novel but simple approach based on selecting a single feature for which the anomaly value is the maximum. The proposed approach applied in the original feature space has been evaluated and compared with relevant state-of-the-art AD methods on Target Detection Blind Test data sets. Preliminary results suggest that the proposed method can achieve better detection performance than its counterparts. The results also show that the proposed method is computationally expedient.