Application of Adaptive Watermarking For Efficient Image Annotation for Data Embedding

In this paper we introduce effective data hiding for image annotation, High fidelity is a demanding requirement for data hiding for images with artistic or medical value. This correspondence proposes image watermarking for annotation with robustness to moderate distortion. To achieve the high fidelity of the embedded image, the model is built by mixing the outputs from entropy and a differential localized standard deviation filter. The mixture is then low-pass filtered and normalized to provide a model that produces substantially better perceptual hi-fidelity than existing tools of similar complexity. The model is built by embedding two basic watermarks: a pilot watermark that locate the existence of the watermark and an information watermark that carries a payload of several dozen bits. The objective is to embed 32 bits of metadata into a single image in such a way that it is robust to JPEG compression and cropping.