J-UNIWARD is a popular steganography method for hiding secret messages in JPEG cover images. As a content-adaptive method, J-UNIWARD aims to embed into textured image regions where changes are difficult to detect. To this end, J-UNIWARD first assigns to each DCT coefficient an embedding cost calculated based on the image's Wavelet residual, and then uses a coding method that minimizes the cost while embedding the desired payload. Changing one DCT coefficient affects a 23x23 window of Wavelet coefficients. To speed up the costmap computation, the original implementation pre-computes the Wavelet residual and then considers per changed DCT coefficient a 23x23 window of the Wavelet residual. However, the implementation accesses a window accidentally shifted by one pixel to the bottom right. In this report, we evaluate the effect of this off-by-one error on the resulting costmaps. Some image blocks are over-priced while other image blocks are under-priced, but the difference is relatively small. The off-by-one error seems to make little difference for learning-based steganalysis.

翻译：J-UNIWARD是一种流行的隐写方法，用于在JPEG封面图像中隐藏秘密信息。作为一种内容自适应方法，J-UNIWARD旨在将秘密信息嵌入到纹理丰富的图像区域，这些区域的变化难以被检测。为此，J-UNIWARD首先根据图像的小波残差为每个DCT系数分配嵌入代价，然后使用编码方法在嵌入所需载荷的同时最小化总代价。改变一个DCT系数会影响一个23×23的小波系数窗口。为加速代价图计算，原始实现预先计算小波残差，然后针对每个被改变的DCT系数考虑一个23×23的小波残差窗口。然而，实现中访问的窗口意外地向右下方偏移了一个像素。本报告评估了这一偏移一位错误对最终代价图的影响。部分图像块被高估代价，而另一些图像块被低估代价，但差异相对较小。对于基于学习的隐写分析，这一偏移一位错误似乎影响甚微。