AlgART Java Libraries: arrays and image processing
Welcome to open-source Java libraries, supporting generalized smart arrays and matrices with elements of any types (1 bit, 8/16/32/64-bit integers, 32/64-bit floating point values and any other Java types), including a wide set of 2D-, 3D- and multidimensional image processing and other algorithms, working with arrays and matrices.
These libraries are distributed under the MIT license. So, they can be freely used without any restrictions.
- 63-bit addressing of array elements (all indexes and length are represented by 64-bit
longtype). So, it's theoretically possible to create and process arrays and matrices containing up to 263−1 (~1019) elements of any primitive or non-primitive types, if OS and hardware can provide necessary amount of memory or disk space.
- Memory model concept allows storing AlgART arrays in different schemes, from simple Java arrays to mapped disk files; all necessary data transfers are performed automatically while every access to an element or a block of elements.
- Wide set of image processing algorithms over matrices: linear filtering, mathematical morphology, rank operations, spectral transformation (FFT), etc.
- Most of algorithms are designed for any number of matrix dimensions, so not only 2D, but also 3D image processing, 4D and common multidimensional image processing are supported.
- Wide usage of lazy evaluations: most of typical operations, like elementwise summing or geometrical matrix transformations, are implemented via lazy views of the source array or matrix. For example, you can take a multidimensional matrix, rotate it (or perform any other affine or projective transform), and then extract a submatrix from the result — all these operations will be performed virtually (not requiring time), and actual calculations will be performed only at the moment of accessing elements, usually while copying the resulting matrix to a newly created one. Moreover, in many cases the library will “understand” itself, that the user wants to perform rotation or another transform, and will split the matrix into suitable rectangular blocks (fitting in RAM) and choose the best algorithm for this task at the moment of copying operation.
- Skeletonization and measuring of binary images.
- Built-in multithreading optimization for multi-core processors for most algorithms.
- And more, and more, and more...
These libraries are fully documented by Javadoc: see below.
You can also discuss and comment this project at
Welcome to use AlgART Libraries!
- GIT repository: AlgART on BitBucket
- algart.zip — contains all Java sources and algart.jar (compiled classes) (19 Dec 2013)
- algart-docs.zip — full JavaDocs in a single archive (19 Dec 2013)
If you want to submit these libraries to some directory, here is a link to PAD-file (Portable Application Description) with full product information.