An Improved SPIHT Wavelet Transform in the Underwater Acoustic Image Compression

The constraints of traditional wavelet filters and wavelet coefficients such as it can not be based on the input signal changes, combined with underwater acoustic channel transmission and imaged sonar principles causes the sharp edges or the presence of singular points of piecewise smooth sound effects far from ideal. To deal with these shortcomings, this paper proposes an improved SPIRT algorithm which image most of the energy is concentrated in the low frequency sub-band after wavelet transform. Though SPIRT algorithm diversity redundancy judgment rule which is located in the low frequency sub-band Wavelet coefficients resulting in a code scanning initial zerotree and producing more unnecessary sign bit is relatively large. Using the methods and diversity judgment rules of changing the original algorithm in wavelet tree construction, which can reduce the initial stage of the zero-tree scan number and redundancy of diversity judgments resulting as well as improve the coding efficiency. Matlab language is used to achieve the analysis of underwater acoustic image compression. As the comparing results showed that the improved adaptive wavelet transform algorithm reduce the wavelet transform coefficients to obtain more ideal compression ratio at a certain extent. To ensure the stability of the transformation process, the acoustic image compression method has a good application value.