The ViStaCoRe Coding Package is a Matlab Toolbox for achromatic and color image compression that includes a set of transform coding algorithms based on (1) Human Vision Models of different accuracy, and (2) coefficient selection through Sparse Regression in local frequency domains (in particular SVR). The ViStaCoRe Restoration Package is a Matlab Toolbox for image restoration that includes (1) classical regularization techniques, (2) classical wavelet thresholding techniques, (3) regularization functionals based on non-linear Human Vision models, and (4) denoising techniques based on Kernel regression in wavelet domains.
VistaQualityTools is a Matlab Toolbox for full reference color (and also achromatic) image quality assessment based on divisive normalization Human Vision models in the DCT and the Wavelet domains.
SpatioSpectralTools is a Matlab Toolbox for reflectance and illuminant estimation that uses spatial information to simplify the (otherwise ill-conditioned) inverse problem. The proposed analysis is useful to derive the spatio-spectral resolution (number of spectral sensors and spatial extent of ) required to solve a retrieval problem.
A Matlab Toolbox with convenient functions to handle video data. It includes routines to read VQEG and LIVE databases, generate synthetic sequences with controlled 2d and 3d speed (colored noise, random dots, rigid solid moving in a field, sequences from images), Spatio-temporal Fourier transforms, Perceptual sensors and filters (V1 and MT cells), and spatio-temporal CSFs.
VideoQualityTools is a Matlab Toolbox for perceptual video quality assessment based on the Standard Spatial Observer model augmented with Divisive Normalization. It performed second-best in VQEG Phase-I using no ad-hoc hand-crafted features.
VideoCodingTools is a Matlab Toolbox for motion estimation/compensation and video compression. Optical flow computation is done with perceptually meaningful hierarchical block matching, and residual quantization is done according to non-linear Human Visual System models.