A radar interferometric technique for topographic mapping of surfaces promises a high resolution, globally consistent approach to generation of digital elevation models. One implementation approach, that of utilizing a single synthetic aperture radar system in a nearly repeating orbit, is attractive not only for cost and complexity reasons but also in that it permits inference of changes in the surface over the orbit repeat cycle from the correlation properties of the radar echoes. Here we characterize the various sources contributing to the echo correlation statistics, and isolate the term which most closely describes sur cial change. We then examine the application of this approach to topographic mapping of vegetated surfaces which may be expected to possess varying backscatter over time. We nd that there is decorrelation increasing with time but that digital terrain model generation remains feasible. We present such a map of a forested area in Oregon which also includes some nearly unvegetated lava ows, and nd that temporal decorrelation contributions to the height errors may be limited to 1.5 and 2.6 m for the forested and lava areas, respectively, if suitable attention is given to experiment design. Such a technique could provide a global digital terrain map.

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The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.

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