MSPIHT Based Image Compression for Despeckling Medical Ultrasound Images

Abstract
 A novel technique for despeckling the medical ultrasound images using lossy-less compression is presented. The logarithm of the input image is first transformed to the multiscale wavelet domain. It is then shown that the subband coefficients of the log transformed ultrasound image can be successfully modeled using the generalized Laplacian distribution. Based on this modeling, the uniform threshold quantizer is proposed in order to achieve simultaneous despeckling and quantization. This adaptation is based on: 1) an estimate of the corrupting speckle noise level in the image; 2) the estimated statistics of the noise-free subband coefficients; and     3) the required compression rate.  Context-based classification is also applied to the noisy coefficients to enhance the performance of the subband coder. A BFOS algorithm decides the number of levels assigned to each quantizer. An entropy coder, such as the SPIHT coding scheme, provides the final encoded bit-rate for the minimization requirements.

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