Local Binary Descriptors are becoming more and more popular for image
matching tasks, especially when going mobile. While they are extensively
studied in this context, their ability to carry enough information in order to
infer the original image is seldom addressed.
In this work, we leverage an inverse problem approach to show that it is
possible to directly reconstruct the image content from Local Binary
Descriptors. This process relies on very broad assumptions besides the
knowledge of the pattern of the descriptor at hand. This generalizes previous
results that required either a prior learning database or non-binarized
features.
Furthermore, our reconstruction scheme reveals differences in the way
different Local Binary Descriptors capture and encode image information. Hence,
the potential applications of our work are multiple, ranging from privacy
issues caused by eavesdropping image keypoints streamed by mobile devices to
the design of better descriptors through the visualization and the analysis of
their geometric content.

该论文使用反问题方法，展示了可以通过局部二进制描述直接重构出原始图像的信息，同时还分析了不同的局部二进制描述子编码图像信息的方式，具有在隐私问题和特征设计方面的多种应用。

从位到像：局部二进制描述符的反演

From Bits to Images: Inversion of Local Binary Descriptors

This tutorial paper describes the problem of image reconstruction from
interferometric data with a particular focus on the specific problems
encountered at optical (visible/IR) wavelengths. The challenging issues in
image reconstruction from interferometric data are introduced in the general
framework of inverse problem approach. This framework is then used to describe
existing image reconstruction algorithms in radio interferometry and the new
methods specifically developed for optical interferometry.

本篇论文介绍了从干涉数据中重建图像的问题，具体关注光学（可见 / 红外）波长下遇到的问题。我们提出将干涉数据重建图像的困难问题置于反问题方法的总体框架中进行介绍，然后描述了现有无线电干涉图像重建算法以及针对光学干涉而开发的新方法。