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This paper compares two general and formal solutions to the problem of fusion of multispectral images with high-resolution panchromatic observations. The former exploits the undecimated discrete wavelet transform, which is an octave bandpass representation achieved from a conventional discrete wavelet transform by omitting all decimators and upsampling the(More)
This paper presents an image fusion method suitable for pan-sharpening of multispectral (MS) bands, based on nonseparable multi-resolution analysis (MRA). The low-resolution MS bands are resampled to the fine scale of the panchromatic (Pan) image and sharpened by injecting highpass directional details extracted from the high-resolution Pan image by means of(More)
This paper introduces a novel approach for evaluating the quality of pansharpened multispectral (MS) imagery without resorting to reference originals. Hence, evaluations are feasible at the highest spatial resolution of the panchromatic (PAN) sensor. Wang and Bovik's image quality index (QI) provides a statistical similarity measurement between two(More)
A novel method for estimating the shape factor of a generalized Gaussian probability density function (PDF) is presented and assessed. It relies on matching the entropy of the modeled distribution with that of the empirical data. The entropic approach is suitable for real-time applications and yields results that are accurate also for low values of the(More)
This work presents a general and formal solution to the problem of fusion of a multi-spectral (MS) image with a higher-resolution panchromatic (P) observation. The method relies on the generalised Laplacian pyramid, which is an over-sampled structure obtained by subtracting from an image its low-pass version. The goal is to selectively performs(More)
In this work, near-lossless compression yielding strictly bounded reconstruction error is proposed for high-quality compression of remote sensing images. A classified causal DPCM scheme is presented for optical data, either multi/hyperspectral three-dimensional (3-D) or panchromatic two-dimensional (2-D) observations. It is based on a classified(More)