The effects of invisible watermarking on satellite image classification

Abstract

Remotely sensed satellite images are an important source of geographical data commonly used as input for various types of classification algorithms. For example, these algorithms are commonly used to classify earth land cover, analyze crop conditions, assess mineral and petroleum deposits, and quantify urban growth. Many vendors of digital images are using or are considering the use of invisible watermarking as a means of protecting their images from theft or unauthorized usage. Indeed, the use of invisible watermarking is routinely considered for use in emerging digital rights management~(DRM) systems that may be deployed to manage and protect the rights associated with satellite imagery, or types of "scientific" imagery~(e.g., in the medical field) that routinely have mathematical analyses applied to them. The concern then is how this watermarking impacts subsequent analyses. Specifically, the invisible watermarking process involves making imperceptible modifications to the pixel values of an image. However, even though these changes may be imperceptible to the human observer, they must be of sufficient magnitude to allow for watermark detection. Because of this, the use of invisible watermarking can also impact the performance of image classification algorithms. This paper is concerned with quantifying the impact that invisible watermarks have on satellite image classification. In particular, Landsat satellite images were watermarked using a number of well-known techniques, and the misclassification that resulted from this watermarking was measured. Experimental results show that even weak watermarking can lead to significant misclassification when common image classification algorithms are applied. Thus, the use of watermarking within DRM systems needs to be carefully considered, with particular attention given to the type of content that the watermarking will be applied to.