基于SPIHT和视觉显著性检测的彩色图像水声信道传输

在学术和工程领域，如何在带宽严重受限的水声信道中获取具有一定可用性的彩色图像一直是一个备受关注的问题。文章提出了一种新的水下彩色图像传输方法，利用基于分级树集合分裂(Set Partitioning in HierarchicalTrees, SPIHT)算法的图像渐进传输和视觉显著性检测，在复杂多变、带宽严重受限的水声信道中获得可用性较好的水下彩色图像。该方法根据信噪比动态调整数据传输方案，并使用红色通道补偿来提高频域中显著性检测的准确性。然后使用 SPIHT 渐进传输图像，并在接收端通过导向滤波解决高降采样率引起的块效应，以获得高质量的水下图像。实验结果表明，所提出的方法在压缩水下彩色图像方面具有一定的适用性。

Color image transmission in underwater acoustic channel based on SPIHT and visual saliency detection

In both the academic and engineering fields, the pursuit of obtaining color images with certain availability in severely bandwidth-constrained underwater acoustic channels is a matter of great interest and attention. In this paper, a new method for underwater color image transmission is proposed, which utilizes the set partitioning in hierarchical trees (SPIHT) algorithm based progressive image transmission and visual salience detection to achieve underwater color images with better availability in complex and highly bandwidth-constrained underwater acoustic channels. The method dynamically adjusts the data transmission scheme based on the signal-to-noise ratio and employs red channel compensation to enhance the accuracy of saliency detection in the frequency domain. Subsequently, the SPIHT is used for progressive image transmission, and the block artifacts caused by high down sampling rates are addressed by using guided filtering at the receiver end to obtain high-quality underwater images. Experimental results demonstrate the applicability of the proposed method in compressing underwater color images.