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An ISAR image self-adaptive quantization method based on histogram entropy

ActiveCN117491997BReduce the scale of operationsavoid computation
The application discloses an ISAR image adaptive quantization method based on histogram entropy, and belongs to the technical field of radars. An M*N dimension ISAR amplitude floating-point data matrix model in units of dB is firstly constructed; then a quantization boundary value coordinate axis of the ISAR image quantization is constructed; then the optimal upper and lower quantization boundaries of the ISAR amplitude data are obtained; finally, the optimal quantization image is obtained by quantization based on the obtained upper and lower quantization boundaries. The application uses the entropy of the ISAR image as an evaluation index of adaptive quantization, has universal applicability, and reduces the problem of non-uniform quantization of different targets, different resolutions and different signal-to-noise ratio environments during ISAR imaging. By using the histogram entropy of the ISAR image, the calculation amount of the entropy operation of the whole image is avoided, and only the histogram needs to be quantized, so that the operation scale of the two-dimensional image is reduced to the scale of the quantization order W, and the engineering application of real-time processing is more favorable. The histogram entropy can be used for different quantization bit numbers.
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