In the wild, wireless multimedia sensor network (WMSN) communication has limited\nbandwidth and the transmission of wildlife monitoring images always suffers signal interference,\nwhich is time-consuming, or sometimes even causes failure. Generally, only part of each wildlife\nimage is valuable, therefore, if we could transmit the images according to the importance of the\ncontent, the above issues can be avoided. Inspired by the progressive transmission strategy, we\npropose a hierarchical coding progressive transmission method in this paper, which can transmit\nthe saliency object region (i.e. the animal) and its background with different coding strategies and\npriorities. Specifically, we firstly construct a convolution neural network via the MobileNet model for\nthe detection of the saliency object region and obtaining the mask on wildlife. Then, according to\nthe importance of wavelet coefficients, set partitioned in hierarchical tree (SPIHT) lossless coding\nis utilized to transmit the saliency image which ensures the transmission accuracy of the wildlife\nregion. After that, the background region left over is transmitted via the Embedded ZerotreeWavelets\n(EZW) lossy coding strategy, to improve the transmission efficiency. To verify the efficiency of our\nalgorithm, a demonstration of the transmission of field-captured wildlife images is presented. Further,\ncomparison of results with existing EZW and discrete cosine transform (DCT) algorithms shows\nthat the proposed algorithm improves the peak signal to noise ratio (PSNR) and structural similarity \nindex (SSIM) by 21.11%, 14.72% and 9.47%, 6.25%, respectively.
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