Kernel regression is an effective tool for a variety of image processing tasks such as denoising and interpolation [1]. In this paper, we extend the use of kernel regression for de...
Images are conventionally sampled on a rectangular lattice, and they are also commonly stored as such a lattice. Thus, traditional image processing is carried out on the rectangula...
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensio...
In this paper, we explore the application of 2-D dual-tree discrete wavelet transform (DDWT), which is a directional and redundant transform, for image coding. Three methods for sp...
In this paper, we exploit a recently introduced coding algorithm called multidimensional multiscale parser (MMP) as an alternative to the traditional transform quantization-based m...
Nuno M. M. Rodrigues, Eduardo A. B. da Silva, Muri...
We introduce a novel synthetic-aperture imaging method for radar systems that rely on sources of opportunity. We consider receivers that fly along arbitrary, but known, flight traj...
In this work, we investigate how illuminant estimation techniques can be improved, taking into account automatically extracted information about the content of the images. We consi...
In many practical distributed source coding (DSC) applications, correlation information has to be estimated at the encoder in order to determine the encoding rate. Coding efficien...
In this paper, a novel method for reducing the runtime complexity of a support vector machine classifier is presented. The new training algorithm is fast and simple. This is achiev...
Abstract--In digital imaging applications, data are typically obtained via a spatial subsampling procedure implemented as a color filter array--a physical construction whereby only...