snaphu 2.0.7-1 source package in Ubuntu

Changelog

snaphu (2.0.7-1) unstable; urgency=medium

  * New upstream release.
  * Update dates in d/copyright.
  * debian/patches:
    - Refresh all patches.

 -- Antonio Valentino <email address hidden>  Thu, 28 Mar 2024 09:00:06 +0000

Upload details

Uploaded by:
Debian GIS Project
Uploaded to:
Sid
Original maintainer:
Debian GIS Project
Architectures:
any
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Oracular release multiverse misc

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File Size SHA-256 Checksum
snaphu_2.0.7-1.dsc 2.0 KiB b6f7e7d3a9e7557f9b495bdf1acc54dd728a7cc7b3a3d8f0a6096b356bb8d58a
snaphu_2.0.7.orig.tar.gz 167.2 KiB c03ac126f9a964321bb5d6fb5b4004728368da268d7cb8407bb295a8abe5b262
snaphu_2.0.7-1.debian.tar.xz 6.3 KiB efbfe181f841be0785ac68d4fb3d963f1b7535355e404dd4f23773a7e99f2414

Available diffs

No changes file available.

Binary packages built by this source

snaphu: Statistical-Cost, Network-Flow Algorithm for 2D Phase Unwrapping

 Two-dimensional phase unwrapping is the process of recovering
 unambiguous phase data from a 2-D array of phase values known only
 modulo 2pi rad.
 .
 There are many applications, like Magnetic Resonance Imaging (MRI),
 Synthetic Aperture Radar (SAR), fringe pattern analysis, tomography
 and spectroscopy, which as part of their fundamental operation depend
 upon the extraction of a phase signal from their input image. Usually
 the phase is available in a form that suffers from 2-pi phase jumps
 due to the use of the mathematical arctangent function, which produces
 an inherently wrapped output. This wrapped phase is unusable until the
 phase discontinuities are removed.
 .
 SNAPHU is an implementation of the Statistical-cost, Network-flow
 Algorithm for Phase Unwrapping particularly suitable for SAR
 interferometry applications. This algorithm poses phase unwrapping as
 a maximum a posteriori probability (MAP) estimation problem, the
 objective of which is to compute the most likely unwrapped solution
 given the observable input data. Because the statistics relating the
 input data to the solution depend on the measured quantity, SNAPHU
 incorporates three built-in statistical models, for topography data,
 deformation data, and smooth generic data. The posed optimization
 problem is solved approximately with use of network-flow techniques.
 .
 As SNAPHU uses an iterative optimization procedure, its execution time
 depends on the difficulty of the interferogram. In single-tile mode
 the required memory is on the order of 100 MB per 1000000 pixels in
 the input interferogram.

snaphu-dbgsym: debug symbols for snaphu