In realistic outdoor scenarios, image sensors tend to suffer from various weather conditions (e.g., haze, rain, etc.),which make the images of the same scene taken at different times may be different. Therefore, one should be able to securely embed secret messages into these images by making use of the variations of the weather effects. Inspired by some recent natural steganography algorithms, this paper presents a novel haze image steganography method, which embeds messages through adjusting the weather effects of an input haze image, making it resemble the same image captured under another weather condition. The proposed steganography method consists of three parts: (1) model parameter estimation of the input haze image, (2) haze effects adjustment according to the atmospheric scattering model, (3) message embedding using the floating-point adjusted haze image. 10,000 haze images captured under different haze conditions in various scenarios were used to test the proposed steganography algorithm. The experimental results show that the proposed steganography algorithm is more secure than S-UNIWARD and HILL for steganalyzers who only have raw haze images.

在现实的室外场景中，图像传感器倾向于遭受各种天气条件（例如，阴霾，雨水等）的影响，这使得在不同时间拍摄的同一场景的图像可能不同。因此，人们应该能够通过利用天气影响的变化将秘密消息安全地嵌入这些图像中。受到最近一些自然隐写术算法的启发，本文提出了一种新颖的雾霾图像隐写术方法，该方法通过调整输入的雾霾图像的天气影响嵌入消息，使其类似于在另一种天气条件下捕获的相同图像。所提出的隐写方法由三部分组成：（1）输入雾度图像的模型参数估计；（2）根据大气散射模型调整雾度效果；（3）使用浮点调整后的雾度图像嵌入消息。在各种情况下，在不同雾度条件下捕获的10,000个雾度图像用于测试所提出的隐写算法。实验结果表明，对于仅具有原始雾度图像的隐写分析仪，该隐写算法比S-UNIWARD和HILL更安全。