* Various extensions to Local Minima and Maxima (3D algorithms, on-the-fly
thresholding).
* Added vigra::BucketQueue, vigra::MappedBucketQueue.
* Refactored and extended 2D watershed algorithms (especially
watershedsRegionGrowing()).
* Added the vigra::Quaternion class.
* Added Unsupervised Decomposition.
* Added mathematical functions (even(), odd(), gamma(), loggamma(), legendre(),
besselJ(), besselY(), linearSequence(), indexSort(), inversePermutation(),
applyPermutation(), checksum())
* Implemented wrapper of the FFTW library to support arbitrary dimensional
Fourier transforms (see fourierTransform() and vigra::FFTWPlan) and FFT-based
convolution (see convolveFFT() and vigra::FFTWConvolvePlan) and refactored
vigra::FFTWComplex.
* Added cannyEdgelListThreshold(), cannyEdgelList3x3Threshold().
* Added capability to handle subarrays and anisotropic resolution to
separableConvolveMultiArray() and related Gaussian filters. Added windowRatio
parameters to vigra::Kernel1D::initGaussian() and
vigra::Kernel1D::initGaussianDerivative()
* Added vigra::StridedScanOrderIterator and corresponding
vigra::MultiArrayView::begin().
* Extended vigra::MultiArrayView. Added vigra::Shape1 ... vigra::Shape5
convenience typedefs.
* Implemented vigra::multi_math (arithmetic and algebraic functions for
multi-dimensional arrays).
* Extended the vigra::HDF5File class.
* Improved and documented the Timing macros for runtime measurements.
* Added support for the OpenEXR image format and multi-page TIFF. Improved
support for the SIF format.
* vigranumpy: added axistags and completly re-implemented VigraArray and the
conversion between Python and C++ arrays in terms of axistags.
* Minor improvements and bug fixes in the code and documentation.
* Fixed the build process for MacOS X.
* Re-activeted vigra-config (script to query VIGRA installation information)
and added VigraConfig.cmake (query VIGRA installation information from within
cmake).
* Added CDash support (nightly builds and tests).
* Added convexHull().
* Added vigra::Box.
* Added vigra::Sampler class to sample given data in various ways.
* Added much new functionality to the vigra::RandomForest class (e.g. more
split strategies, variable importance measures, feature selection)
* Added readSIF() (reader for the Andor SIF file format).
* Added vigra::HDF5File for easier navigation in HDF5 files.
* Added recursive approximation of the Gaussian filter
(recursiveGaussianFilterX(), recursiveGaussianFilterY())
* vigranumpy: added Gabor filtering.
* Fixed multi-threading bugs at various places.
* Minor improvements and bug fixes in the code and documentation.
VIGRA is a computer vision library that puts its main emphasize on
flexible algorithms, because algorithms represent the principle know-how
of this field. The library was consequently built using generic
programming as introduced by Stepanov and Musser and exemplified in the
C++ Standard Template Library. By writing a few adapters (image iterators
and accessors) you can use VIGRA's algorithms on top of your data
structures, within your environment. Alternatively, you can also use the
data structures provided within VIGRA, which can be easily adapted to a
wide range of applications. VIGRA's flexibility comes almost for free:
Since the design uses compile-time polymorphism (templates), performance
of the compiled program approaches that of a traditional, hand tuned,
inflexible, solution.
