Wavelet-based watermarking of remotely sensed imagery tailored to classification performance

Abstract

Watermarking is widely being explored as a means of providing protection of ownership rights for multimedia data, and there has been increasing interest in applying watermarking to remotely sensed data for this same purpose. However, watermarking techniques developed for multimedia cannot be applied directly to remotely sensed data due the fact that the analytic integrity of the data, rather than perceptual quality, is of primary importance. In this paper, a watermarking technique for remotely sensed data based on the discrete wavelet transform (DWT) is proposed, and its impact on unsupervised classification as well as attacks such as cropping is studied.