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Pixel compression

The advantage of this transform is that its kernel f(s, x, x) is left unspecified. The discrete wavelet transform was invented by Haar125, used by petroleum geologists to extract meaningful data from noisy seismograms, and later utilized in JPEG2000 pixel compression. [Pg.109]

Pattern recognition can be classified according to several parameters. Below we discuss only the supervised/unsupervised dichotomy because it represents two different ways of analyzing hyperspectral data cubes. Unsupervised methods (cluster analysis) classify image pixels without calibration and with spectra only, in contrast to supervised classifications. Feature extraction methods [21] such as PCA or wavelet compression are often applied before cluster analysis. [Pg.418]

Experiments were performed using a titanium sapphire laser oscillator capable of producing pulses with bandwidths up to 80 nm FWHM. The output of the oscillator was evaluated to make sure there were no changes in the spectrum across the beam and was compressed with a double prism pair arrangement. The pulse shaper uses prisms as the dispersive elements, two cylindrical concave mirrors, and a spatial light modulator (CRI Inc. SLM-256), composed of two 128-pixel liquid crystal masks in series. The SLM was placed at the Fourier plane [5]. After compression and pulse shaping, 200 pJ pulses were used to interrogate the samples. [Pg.95]

The MIFs obtained from qrtochrome enzymes are subsequently transformed and simplified as shown in Fig. 12.4. A three-dimensional grid map (3D map) may be viewed as a 3D matrix that contains forces of attraction and repulsion between a chemical probe and a protein. A 3D map is an image of the CYP-probe molecular interactions in which each pixel contains information about the cartesian coordinates and a physicochemical interaction. In cytochrome, where a catalytic reaction has to take place, all the 3D map information can be compressed and refers to the... [Pg.280]

Figure 2.11 illustrates this two-step procedure for compressed data sets in the spectral (right) and spatial (left) directions. Taking as an example the compression in the spectral direction, resolution is first carried out on the compressed data set, Dcomp. where all pixels are preserved and the number of spectral charmels is... [Pg.95]

Figure 2.12 Left Resolution results after image compression by binning in the spectral direction. Center Resolution results from full image analysis. Right Resolution results after Image compression in the pixel direction by taking a pixel subset around SIMPLISMA purest selected pixels. Figure 2.12 Left Resolution results after image compression by binning in the spectral direction. Center Resolution results from full image analysis. Right Resolution results after Image compression in the pixel direction by taking a pixel subset around SIMPLISMA purest selected pixels.
Noordam et al. [53] used a multispectral imager composed of a PbS camera and a filter wheel (680, 740, 800, 840, 1010, lllOnm) for viewing two wooden disks of pine and sprace wood (Figure 8.11). Based on PGA on single pixels, these authors were able to map three regions, namely bark wood, compression wood and normal wood. [Pg.286]

Also, the DCT can be computed very efficiently with a time-complexity 0(N log N) as opposed to O(N ) for the case of the KLT. The computation can be made even more very efficient by blocking the image into K square blocks, each block with /lT x x/N pixels where N = K" N (i.e. create disjoint blocks of sub-images of, say, 8 x 8 or 16 x 16 pixels), thereby reducing the DCT computations to each block. This makes the DCT the preferred algorithm in many standard eommercial compression algorithms such as JPEG. [Pg.464]

Integatlon of binary raster images of line drawings in a databank is state-of-the-art and problems related to a pixel representation of Images (facsimile encoding) are well-known. Particularly, compression of the voluminous data files is needed. [Pg.144]

As transmission bandwidth is costiy it is useful to represent each image using as little bits as possible. Reversible (or lossless) compression methods look for patterns among the bits of the image that can be encoded more succinctiy. For example, if a number of adjacent pixels have the same value, this fact can be encoded using fewer bits than it takes to list those values a number of times. However, in radiological practice the gain is only moderate, about a factor of 2... [Pg.139]


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Pixel

Pixel, pixels

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