1,700 research outputs found

    Optimal Compression of Floating-point Astronomical Images Without Significant Loss of Information

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    We describe a compression method for floating-point astronomical images that gives compression ratios of 6 -- 10 while still preserving the scientifically important information in the image. The pixel values are first preprocessed by quantizing them into scaled integer intensity levels, which removes some of the uncompressible noise in the image. The integers are then losslessly compressed using the fast and efficient Rice algorithm and stored in a portable FITS format file. Quantizing an image more coarsely gives greater image compression, but it also increases the noise and degrades the precision of the photometric and astrometric measurements in the quantized image. Dithering the pixel values during the quantization process can greatly improve the precision of measurements in the images. This is especially important if the analysis algorithm relies on the mode or the median which would be similarly quantized if the pixel values are not dithered. We perform a series of experiments on both synthetic and real astronomical CCD images to quantitatively demonstrate that the magnitudes and positions of stars in the quantized images can be measured with the predicted amount of precision. In order to encourage wider use of these image compression methods, we have made available a pair of general-purpose image compression programs, called fpack and funpack, which can be used to compress any FITS format image.Comment: Accepted PAS

    Lossless Astronomical Image Compression and the Effects of Noise

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    We compare a variety of lossless image compression methods on a large sample of astronomical images and show how the compression ratios and speeds of the algorithms are affected by the amount of noise in the images. In the ideal case where the image pixel values have a random Gaussian distribution, the equivalent number of uncompressible noise bits per pixel is given by Nbits =log2(sigma * sqrt(12)) and the lossless compression ratio is given by R = BITPIX / Nbits + K where BITPIX is the bit length of the pixel values and K is a measure of the efficiency of the compression algorithm. We perform image compression tests on a large sample of integer astronomical CCD images using the GZIP compression program and using a newer FITS tiled-image compression method that currently supports 4 compression algorithms: Rice, Hcompress, PLIO, and GZIP. Overall, the Rice compression algorithm strikes the best balance of compression and computational efficiency; it is 2--3 times faster and produces about 1.4 times greater compression than GZIP. The Rice algorithm produces 75%--90% (depending on the amount of noise in the image) as much compression as an ideal algorithm with K = 0. The image compression and uncompression utility programs used in this study (called fpack and funpack) are publicly available from the HEASARC web site. A simple command-line interface may be used to compress or uncompress any FITS image file.Comment: 20 pages, 9 figures, to be published in PAS

    Helicoidal surfaces with constant anisotropic mean curvature

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    We study surfaces with constant anisotropic mean curvature which are invariant under a helicoidal motion. For functionals with axially symmetric Wulff shapes, we generalize the recently developed twizzler representation of Perdomo to the anisotropic case and show how all helicoidal constant anisotropic mean curvature surfaces can be obtained by quadratures

    Independence Distribution Preserving Covariance Structures for the Multivariate Linear Model

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    AbstractConsider the multivariate linear model for the random matrixYn×p∼MN(XB,V⊗Σ), whereBis the parameter matrix,Xis a model matrix, not necessarily of full rank, andV⊗Σ is annp×nppositive-definite dispersion matrix. This paper presents sufficient conditions on the positive-definite matrixVsuch that the statistics for testingH0:CB=0vsHa:CB≠0have the same distribution as under the i.i.d. covariance structureI⊗Σ

    TB56: Effects of Differing Abundance Levels of Aphids and of Certain Virus Diseases upon Yield and Virus Disease Spread in Potatoes

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    In eight years during the period 1944 to 1954, a study was conducted on Aroostook Farm, Presque Isle, Maine, to develop ways of obtaining and maintaining varying levels of aphid abundance on potato plants. Methods for measuring aphid abundance and their effects on yield and virus transmission were devised. These techniques were then used to determine the effects of varying all-season levels of abundance of the aphids and of virus reservoirs of two potat o diseases upon yield of potatoes and the spread of leaf roll and spindle tuber in four varieties of potatoes. The results of that study are reported in this bulletin.https://digitalcommons.library.umaine.edu/aes_techbulletin/1129/thumbnail.jp

    Earliest Archaeological Evidence of Persistent Hominin Carnivory

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    The emergence of lithic technology by ∼2.6 million years ago (Ma) is often interpreted as a correlate of increasingly recurrent hominin acquisition and consumption of animal remains. Associated faunal evidence, however, is poorly preserved prior to ∼1.8 Ma, limiting our understanding of early archaeological (Oldowan) hominin carnivory. Here, we detail three large well-preserved zooarchaeological assemblages from Kanjera South, Kenya. The assemblages date to ∼2.0 Ma, pre-dating all previously published archaeofaunas of appreciable size. At Kanjera, there is clear evidence that Oldowan hominins acquired and processed numerous, relatively complete, small ungulate carcasses. Moreover, they had at least occasional access to the fleshed remains of larger, wildebeest-sized animals. The overall record of hominin activities is consistent through the stratified sequence – spanning hundreds to thousands of years – and provides the earliest archaeological evidence of sustained hominin involvement with fleshed animal remains (i.e., persistent carnivory), a foraging adaptation central to many models of hominin evolution
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