Content layer progressive coding of digital maps.

A new lossless context based method is presented for content progressive coding of limited bits/pixel images, such as maps, company logos, etc., common on the World Wide Web. Progressive encoding is achieved by encoding the image in content layers based on color level or other predefined information.

Multiset canonical correlations analysis and multispectral, truly multitemporal remote sensing data.

This paper describes two- and multiset canonical correlations analysis (CCA) for data fusion, multisource, multiset, or multitemporal exploratory data analysis. These techniques transform multivariate multiset data into new orthogonal variables called canonical variates (CVs) which, when applied in remote sensing, exhibit ever-decreasing similarity (as expressed by correlation measures) over sets consisting of 1) spectral variables at fixed points in time (R-mode analysis), or 2) temporal variables with fixed wavelengths (T-mode analysis). The CVs are invariant to linear and affine transformations of the original variables within sets which means, for example, that the R-mode CVs are insensitive to changes over time in offset and gain in a measuring device.

Filters involving derivatives with application to reconstruction from scanned halftone images.

This paper presents a method for designing finite impulse response (FIR) filters for samples of a 2-D signal, e.g., an image, and its gradient.