Signal Processing

This dataset is accompanying the manuscript "Lossless archiving view arrays from plenoptic cameras when camera sensor images are available" by Ioan Tabus and Emanuele Palma, published in ISSCS 2021 in July 2021. It is also supporting part of the work carried out in “Lossless Compression of Plenoptic Camera Sensor Images” by Ioan Tabus and Emanuele Palma, published in IEEE Access in February 2021. It contains the archives and the programs for reconstructing the light field datasets publicly used in two major challenges for light field compression.

Participants were 61 children with ADHD and 60 healthy controls (boys and girls, ages 7-12). The ADHD children were diagnosed by an experienced psychiatrist to DSM-IV criteria, and have taken Ritalin for up to 6 months. None of the children in the control group had a history of psychiatric disorders, epilepsy, or any report of high-risk behaviors.

As one of the research directions at OLIVES Lab @ Georgia Tech, we focus on recognizing textures and materials in real-world images, which plays an important role in object recognition and scene understanding. Aiming at describing objects or scenes with more detailed information, we explore how to computationally characterize apparent or latent properties (e.g. surface smoothness) of materials, i.e., computational material characterization, which moves a step further beyond material recognition.

The Costas condition on a permutation matrix, expressed as row indices as elements of a vector c, can be expressed as A*c=b, where b is a vector of integers in which no element is zero.  A particular formulation of the matrix A allows a singular value decomposition in which the eigenvalues are squared integers and the eigenvalues may be scaled to vectors with all integer elements.  This is a database of the Costas constraint matrices A, the scaled eigenvectors, and the squared eigenvalues for orders 3 through 100.