This directory contains two software packages for model-based iterative reconstruction (MBIR) tomography. It includes code for STEM/TEM recon of bright and darkfield data, and 3-D/4-D synchrotron recon code. It also contains some old lagancy code packages.
Plug-and-Play Priors for Interpolation and Reconstruction
This links to software packages for easy-to-use Plug-and-Play implementations. Simple examples with data are giving for sparse interpolation and tomographic reconstruction.
SMAP segmentation software
Robust and computationally efficient software for segmenting images using a Bayesian multiscale framework. It uses the Cluster software above as a basis for characterizing the region classes. The package includes TEST IMAGES from associated publications.
Sparse Matrix Transform (SMT) code and publications
The SMT is a generalization of the FFT and orthonormal wavelet transform that can be used for covariance estimation and fast matrix-vector product computation. It is particularly well suited for non-stationary random processes and time(space)-varying systems analysis.
Color Quantization Software
This directory contains a software packages for performing color quantization of color images using the binary splitting method.
Color document descreening softwared known as Resolution Synthesis based Descreening as described in the IEEE TIP March 2007 paper.
Document Text Segmentation for MRC Coding
This software uses a combination of block-based segmentation known as cost-optimized segmentation (COS) and MRF based classification known as connected-components classification (CCC) to detect and segment text from raster document images.
YCxCz Fidelity Metrics Software
This is a Matlab package for computing two fidelity metrics based on the YCxCz color transformation. One quality metric is based on a non-linear transformation to an Lab-like space, and the other transform is based on a linearized Lab space. Both metrics incoporate a modulation transfer function for the human visual system.
Clustered Component Analysis (CCA)
An Algorithm for Estimating Component Directions in Data. This matlab coding is designed to automatically estimate the number and directions of distinct non-orthogonal components in multivariate data. It can be used in a manner similar to independent components analysis (ICA), but it is based on an explict signal and noise model, and it performs maximum likihood (ML) parameter estimation using the expectation maximization (EM) algorithm. Its algorithmic structure is similar to that used in the Cluster algorithm above.
Tree-Structured Predictor Program C source code that implements an algorithm for nonlinear prediction using a tree-structured predictor. The code consists of two basic programs/algorithms. The first algorithm estimates the order (size) and parameters of a tree using a growing (splitting) and cross-validation pruning strategy. The second program/algorithm then applies the estimated tree parameters to efficiently compute nonlinear estimates from vector inputs.
Software for browsing and searching large image databases efficiently. This is a robust and useful application which runs on win95/98, NT, and unix. It also includes C++ source code, so it can be modified for other applications.
This directory contains software that implements an algorithm for fast space-varying convolution using the matrix source coding technique.
Raster Document Test Images
A 400 dpi and 600 dpi version of a mixed raster document for use in testing document compression algorithms.
Image read and write C-code
Easy to use C-subroutines for reading and writing TIFF and JPEG images.
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