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Topic: Deconvolution

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	Intro. to Signal Processing:Deconvolution (Site not responding. Last check: 2007-10-08)
		Deconvolution is the converse of convolution in the sense that division is the converse of multiplication.
		Deconvolution is used here to remove the distorting influence of an exponential tailing response function from a recorded signal (Window 1, top left) that is the result of an unavoidable RC low-pass filter action in the electronics.
		A different application of the deconvolution function is to reveal the nature of a data transformation function that has been previously applied to a data set by the measurement instrument itself.
	www.wam.umd.edu /~toh/spectrum/Deconvolution.html (385 words)

	Deconvolution - Wikipedia, the free encyclopedia
		Deconvolution is a process used to reverse the effects of convolution on recorded data.
		The concept of deconvolution is widely used in the techniques of signal processing and image processing.
		Deconvolution is also practical to sharpen images that suffer from fast motion or jiggles during capturing.
	en.wikipedia.org /wiki/Deconvolution (1131 words)

	Biotechnology Resource Center - Deconvolution - Microscopy, Imaging and Fluorimetry
		Deconvolution removes out-of-focus light from a z-series of images obtained on a wide field fluorescence microscope using a mathematical process with a result similar to using confocal microscopy.
		The blind deconvolution algorithm used by AutoDeblur is model-based, nonlinear, iterative and constrained.
		Briefly, this means that it is based on a proper physical model of the optics, is iterative in the sense that it repeats the same computational operations many times while converging to the enhanced image solution, and it constrains the fluorescence intensity to be nonnegative.
	www.brc.cornell.edu /brcinfo/?p=decon (707 words)

	CNIC Deconvolution
		Deconvolution of imaged data is essential for accurate 3D reconstructions.
		Our Onyx 3400 has available the Auto-Deblur(Auto-Quant Imaging Inc.) blind deconvolution system which uses an estimated and iteratively refined theoretical point spread function(PSF) that can be adjusted locally to account for variations in refractive characteristics of the tissue with depth and sample characteristics.
		B: After deconvolution with Auto-Deblur, excellent reduction of blurring along the Z axis allows morphology of individual spines superimposed on previously oversaturated dendritic trunks to be resolved.
	www.mssm.edu /cnic/deconvolution.html (179 words)

	BioMed Central \| Full text \| Computational expression deconvolution in a complex mammalian organ
		Deconvoluting expression patterns in a complex tissue using cell type-specific gene lists is dependent on the extent to which the genes selected are expressed at a constant level on a per-cell basis over a range of biological conditions.
		Consistent with this, expression deconvolution analysis estimated that the mammary gland at these stages is composed primarily of brown and white adipose tissue, with only a small amount (<5%) of epithelium (Figure 1b).
		As reflected both by morphology and expression deconvolution estimates, the proportion of epithelial cells peaks during late pregnancy and lactation (Figure 1b, 2a, and 2b).
	www.biomedcentral.com /1471-2105/7/328 (9344 words)

	[No title]
		Deconvolution is a computer method that removes out-of-focus haze from your microscopic images.
		In addition to being easier to use, blind deconvolution technology is better than other deconvolution methods because it adapts to changes in the point-spread due to variations in the refractive index, and the microscope optics.
		Blind deconvolution can be used to better visualize thick samples (3-D data), effectively improving the sensitivity and axial resolution of your microscope, allowing you to better detect fine structures, and perform more accurate morphometry.
	www.p3i.com /deconvol.htm (266 words)

	[No title] (Site not responding. Last check: 2007-10-08)
		Deconvolution is a process universally applied to seismic data, but is one that is mysterious to many geoscientists.
		Deconvolution compresses the basic wavelet in the recorded seismogram and attenuates reverberations and short-period multiples.
		Predictive deconvolution uses the later portions of the autocorrelation to remove the effects of some multiples.
	www.aapg.org /explorer/geophysical_corner/2004/04gpc.cfm (614 words)

	Blind Deconvolution Page
		Blind Deconvolution is a technique which permits recovery of the target object from set of ``blurred'' images in the presence or a poorly determined or unknown point spread function (PSF).
		The results of applyind the blind deconvolution algorithm to each of the four data sub-sets using the twenty highest Strehl ratio frames in each sub-set, is shown in figure 2.
		Figure 1: Application of blind deconvolution to an average compensated image of a binary star using the wavefront-sensor derived PSF as the initial PSF estimate.
	www.ls.eso.org /lasilla/Telescopes/360cat/adonis/Idac/bd/bd.html (1536 words)

	softWoRx Help: Image Restoration Application Notes
		In a one sentence description, the deconvolution residual is a measure of the difference between the measured image and the solution convolved with the PSF.
		For the purpose of digital deconvolution, the residual is calculated from the average of the residuals measured at each point in the three-dimensional image.
		With the aid of the deconvolution image, it is usually possible to understand the structures present in the measured image.
	www.indiana.edu /~elegans/Deconv/DeconAppNotes.html (2390 words)

	Priism Help: Deconvolution
		The deconvolution application does not use the point spread function directly; instead, it accepts a description of either the contrast transfer function (CTF) or the pupil function both of which can be derived from the point spread function.
		Because Priism's deconvolution program will modify the CTF to match different pixel spacings or wavelengths, it is not necessary to use the same pixel spacing and wavelength for imaging the bead and for imaging your normal samples.
		The deconvolution assumes that the mounting media's index of refraction may not match that of the immersion media, but the deconvolution is done as a depth-independent problem using the PSF corresponding to the mean source depth of the imaged volume to deconvolve.
	www.msg.ucsf.edu /IVE/IVE3.3_HTML/Decon.html (6707 words)

	Deconvolution
		Deconvolution, removing instrumental broadening, need not be an untamed operation with many different answers.
		Two are Maximum Likelihood deconvolution methods for data with Poisson (counting) noise statistics, such as encountered in xray spectroscopy.
		Linear deconvolution is sometimes useful because it is fast, and does not enforce positivity.
	www.spectrumsquare.com /sharp.htm (646 words)

	Iterative Deconvolution
		Deconvolution also requires the number of iterations and the low pass filter diameter in pixels.
		The monotonic deconvolution option is based on the heuristic assumption that successive convolutions with the psf will move the pixel values in a monotonically increasing or decreasing direction.
		The deconvolution with a low pass circle diameter of one pixel shows one form of "breakup" that suggestes more regularization is needed.
	www.optinav.com /Iterative-Deconvolution.htm (915 words)

	Systat Software Inc. - PeakFit - HTML Help
		This deconvolution procedure works best with input data that has very little noise, and where peaks would be perfect Gaussians save the impact of the detector.
		Deconvolution is the procedure of undoing that smearing in an effort to see what the data would look like had the instrument perfectly rendered it.
		Deconvolution is fraught with many pitfalls, and the Fourier domain procedure, while simplest, is not always successful.
	www.systat.com /products/PeakFit/help/?sec=1045 (1175 words)

	Numerical Aspects of Deconvolution (via CobWeb/3.1 planetlab1.tamu.edu) (Site not responding. Last check: 2007-10-08)
		The paper describes the inherent difficulties in deconvolution of noisy data, and their efficient numerical treatment.
		The emphasis is on the numerical aspects, and the theory is illustrated with examples.
		Discretizations of deconvolution problems lead to Toeplitz matrices, which are matrices with a very special structure.
	www2.imm.dtu.dk.cob-web.org:8888 /~pch/Regularization/deconv.html (150 words)

	Deconvolution Experiences
		In practice, deconvolution is applied by performing successive Fourier Transforms on an image.
		This had not been a major problem initially because I had not encountered a need to perform both Deconvolution and DDP on an image (either one of these had worked individually depending on the type of image).
		It was immediately clear that both deconvolution and DDP were needed.
	www.astrocruise.com /articles/decon.htm (754 words)

	FAQ, VayTek, Deconvolution, Digital Microscopy, Digital Imaging Systems, VayTek, confocal microscopy, algorithms
		A deconvolution algorithm is a systematic procedure for removing noise or haze from an image.
		Most experts on digital deconvolution agree that at least 90% of the images that can be created with the laser scanning confocal microscope can be produced equally well with digital deconvolution.
		This is because the mathematical formulae for the deconvolution algorithms assume the light in the specimens radiates equally in all directions.
	www.vaytek.com /FAQ.html (5463 words)

	Deconvolution and WIRE
		As a result, all deconvolution algorithms make additional assumptions about the data in an attempt to constrain their solutions, and one must choose an algorithm that is appropriate for the data and what one wants to extract from it.
		The second point is relevant in that point sources are the hardest objects for deconvolution algorithms to reproduce accurately, since they require knowledge of spatial frequencies higher (well, infinite for a true point source) than can be sampled.
		It is not really a deconvolution algorithm per se, but since it is not fourier-based it avoids some of the pitfalls of the other algorithms.
	spider.ipac.caltech.edu /~jason/science/wire_decon.html (1622 words)

	technical note, VayTek, scientific software, Medical Imaging, microscopy, digital imaging, 3-D deconvolution
		Deconvolution methods are the Tikhonov-Miller algorithm (Legandijk, 1990) and the maximum Likelihood Estimation (MLE) (Legandijk, 1990, Conchello and Hansen, 1990; Holmes and Liu, 1991; Csiszar, 1991; Snyder et al., 1992).
		Deconvolution will also not work on an object that is infinitely thin (a few pixels wide).
		Topics include linear and nonlinear methods of deconvolution, specific applications of a proven method, advances made in restoration of images from cell biology and astronomy, and new methods, including maximum probability estimation, Fourier spectrum continuation, and projections onto convex sets.
	www.vaytek.com /technical.html (1541 words)

	Texture Deconvolution
		The algorithm described here employs a deconvolution algorithm to remove these artefacts thereby permitting the Fourier analysis of non-rectangular texture patches.
		However, by applying the texture deconvolution algorithm, it was possible to restore recognition performance to a level approaching that attained for rectangular patches.
		The algorithm provides a Fourier representation that is largely invariant to shape, thereby permitting the analysis of non-rectangular texture patches.
	www.cs.bris.ac.uk /~clark/TextureDeconvolution (265 words)

	GeoCenter - SeisUP - Deconvolution
		Surface Consistent Deconvolution (SCDECON) uses any combination of line, source, receiver, CMP, and offset components to derive accurate deconvolution operators, which are then applied to the input traces.
		Adaptive Deconvolution (ADAPTDCN) is based upon the use of a simple adaptive algorithm which allows continuous updating of the deconvolution operator as the seismic trace is processed.
		Adaptive deconvolution is effective at collapsing refraction, multiple, and surface noise energies.
	www.geocenter.com /seisup/deconvolution.html (449 words)

	BIG - 3D Deconvolution
		The deconvolution task consists in deblurring the observed image in order to recover the original shapes of the object.
		Although 2D deconvolution softwares are available freely, the 3D consideration gives rise to many problems leading to the impossibility to recover the original images without any assumptions.
		In addition, we expect you to include adequate citations and acknowledgments whenever you present or publish results that are based on it.
	bigwww.epfl.ch /demo/deconvolution3D (480 words)

	RIGZONE - Seismic Inversion and Deconvolution, Part B: Dual-Sensor Technology
		A large variety of computer-processing methods are available to transform the observed seismic data into a form that is more useful to the seismic interpreter.
		The purpose of Seismic Inversion and Deconvolution, Part B: Dual-Sensor Technology is to provide the fundamentals of dual-sensor technology.
		By using dual sensors in the acquisition of seismic data, new avenues are opened up that revolutionize all aspects of seismic inversion and deconvolution.
	www.rigzone.com /store/product.asp?p_id=716 (318 words)

	Deconvolution (Site not responding. Last check: 2007-10-08)
		Deconvolution of synthesized images is widely discussed in literature.
		One of the most popular techniques used for deconvolution is the Maximum Entropy Method (MEM) introduced initially by Burg and Ables (1974) for spectral analysis.
		Subsequently MEM was reformalized and improved to provide an efficient technique of deconvolution by Skilling and Gull (1984).
	icarus.uom.ac.mu /nadeem/node17.html (1185 words)

	Deltavision Deconvolution Microscope
		Deconvolution is a software-based process by which one can "re-focus" an out of focus image.
		Deconvolution occurs after image acquisition, and uses nearest-neighbor algorithms to extract information out of blurred regions of an image to clean up these regions - they then appear to be closer to, if not actually in the same plane of focus as the rest of the image.
		A final advantage that deconvolution has over confocal microscopy is that the specimens are illuminated with the white light from a mercury arc lamp that is then passed through a selected optical filter to give the correct excitation wavelength.
	micro.salk.edu /dv/dv.html (1607 words)

	Deconvolution in practice with shapelets
		The PSF deconvolution occurs in the whole shapelets decomposition process.
		The deconvolution heart lies in shapelets_decomp.pro, where the model of the unsmeared galaxy is convolved to the PSF and compared to the observed (smeared) galaxy (while focus is done so as we have a model as accurate as possible).
		This would probably be the most efficient way to obtain an accurate model, but it would need a first iteration of shex on the image, without deconvolution, and then, a second one with deconvolution.
	www.astro.caltech.edu /~jberge/shapelets/manual/manualhtml/node99.html (585 words)

	SVI-wiki: Huygens Deconvolution
		Deconvolution is a mathematical operation used in Image Restoration to recover an image that is degraded by a physical process which can be described by the opposite operation, a convolution.
		An advantage of using measured PSF as in Huygens is that in essence it requires you to calibrate your microscope, and stimulates the use of standard protocols for imaging.
		There is a very simple and clarifying example of a deconvolution done with the Huygens Software in Decon Example.
	support.svi.nl /wiki/HuygensDeconvolution (1729 words)

	Wiener deconvolution - Wikipedia, the free encyclopedia
		Wiener deconvolution is an application of the Wiener filter to the noise problems inherent in deconvolution.
		It works in the frequency domain, attempting to minimize the impact of deconvoluted noise at frequencies which have a poor signal to noise ratio.
		The Wiener deconvolution method has widespread use in image deconvolution applications, as the frequency spectrum of most visual images is fairly well behaved and may be estimated easily.
	en.wikipedia.org /wiki/Wiener_deconvolution (417 words)

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