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Joo, T. H.

Publications and source records attributed to Joo, T. H..

Adaptive Quantizer for Burst Synthetic-Aperture Radar

Adaptive quantizer for burst-mode synthetic-aperture radar reduces data rate of return signal. Device, called block floating-point quantizer (BFPQ) basically analog-to-digital converter that covers wide dynamic range and discards appropriate lower order bits. BFPQ is, in effect, digital approximator with automatic gain control. Moves floatingpoint marker binary representation of signal data in accordance with perceived dynamic range. Available step sizes thus limited to multiples of underlying smallest quantization step (represented by lowest order bit). Retains only first K most significant bits of signal; (L,K) BFPQ is one that does K-bit quantization of signal originally quantized to L bits. Quantization error simply difference between actual signal level and its binary approximation. Other potential applications for BFPQ include speech compression and picture data compression.

Joo, T. H.↗

An adaptive quantization method for burst mode synthetic aperture radar data

Synthetic aperture radar (SAR) has high data rate because it collects and processes the data coherently. The data rate limitation of the system has to be satisfied while maintaining good image quality. Thus, a quantizer with minimum data rate and high SNR should be employed. An adaptive quantization method is proposed for the burst mode SAR. This adaptive quantizer uses uniformly quantized data to select a subset of bits which is equivalent to changing the step size of the uniform quantizer. A simple implementation which uses the previous burst data to compute the local statistics for the bit selection is presented. The use of previous burst simplifies the implementation because it does not require storage or delay; however, an abrupt change in the terrain could result in incorrect bit selection. An error analysis of this implementation and comparison of two burst mode SAR images formed using the uniformly quantized and adaptively quantized data is presented.

Joo, T. H.↗

SAR Speckle Noise Reduction Using Wiener Filter

Synthetic aperture radar (SAR) images are degraded by speckle. A multiplicative speckle noise model for SAR images is presented. Using this model, a Wiener filter is derived by minimizing the mean-squared error using the known speckle statistics. Implementation of the Wiener filter is discussed and experimental results are presented. Finally, possible improvements to this method are explored.

Joo, T. H.↗