Abstract: A new approach to multispectral image compression where the intra- and cross-band correlations are jointly exploited in a surprisingly simple yet very effective manner. The key component of the algorithm is a bijection mapping of the original multispectral image into a virtual 2 dimensional scalar image. By optimally mapping the multispectral image set into a single 2 dimensional array and by subsequently applying a scalar image coding algorithm, the spatial correlation and the spectral correlation of the multispectral data set are jointly exploited. Based on the statistical characteristics of the multispectral data, the bijection mapping can be optimized to minimize the distortion introduced by the compression algorithm. The optimization reduces to the maximization of a function of the second-order statistics of the multispectral data.

Abstract: A clipped metric function is utilized to mitigate the adverse effects of impulsive noise (e.g., lightening, motor vehicle ignition noise) on communications signals. The clipped metric function may be used alone or in conjunction with conventional signal clipping. In one embodiment, a clipped Euclidean metric function is determined as a function of the input signal. The input signal is processed in accordance with the clipped Euclidean metric function, to provide a clipped metric signal. The clipped metric signal is processed in accordance with application dependent requirements. The clipped metric function provides improved performance over conventional signal clipping. For example, utilization of a clipped metric function provides improved performance in situations in which the impulsive noise does not increase the amplitude of the input signal to a level that would be clipped by signal clipping.