  Existing audio watermarking methods usually treat the host audio signals of a
function of time or frequency individually, while considering them in the joint
time-frequency (TF) domain has received less attention. This paper proposes an
audio watermarking framework from the perspective of TF analysis. The proposed
framework treats the host audio signal in the 2-dimensional (2D) TF plane, and
selects a series of patches within the 2D TF image. These patches correspond to
the TF clusters with minimum averaged energy, and are used to form the feature
vectors for watermark embedding. Classical spread spectrum embedding schemes
are incorporated in the framework. The feature patches that carry the
watermarks only occupy a few TF regions of the host audio signal, thus leading
to improved imperceptibility property. In addition, since the feature patches
contain a neighborhood area of TF representation of audio samples, the
correlations among the samples within a single patch could be exploited for
improved robustness against a series of processing attacks. Extensive
experiments are carried out to illustrate the effectiveness of the proposed
system, as compared to its counterpart systems. The aim of this work is to shed
some light on the notion of audio watermarking in TF feature domain, which may
potentially lead us to more robust watermarking solutions against malicious
attacks.
