Embedding complementary imaging data in laser scanning microscopy micrographs by reversible watermarking.

Complementary laser scanning microscopy micrographs are considered as pairs consisting in a master image (MI) and a slave image (SI), the latter with potential for facilitating the interpretation of the MI. We propose a strategy based on reversible watermarking for embedding a lossy compressed version of the SI into the MI. The use of reversible watermarking ensures the exact recovery of the host image. By storing and/or transmitting the watermarked MI in a single file, the information contained in both images that constitute the pair is made available to a potential end-user, which simplifies data association and transfer. Examples are presented using support images collected by two complementary techniques, confocal scanning laser microscopy and transmission laser scanning microscopy, on Hematoxylin and Eosin stained tissue fragments. A strategy for minimizing the watermarking distortions of the MI, while preserving the content of the SI, is discussed in detail.

Adaptive Pairing Reversible Watermarking.

This letter revisits the pairwise reversible watermarking scheme of Ou et al., 2013. An adaptive pixel pairing that considers only pixels with similar prediction errors is introduced. This adaptive approach provides an increased number of pixel pairs where both pixels are embedded and decreases the number of shifted pixels. The adaptive pairwise reversible watermarking outperforms the state-of-the-art low embedding bit-rate schemes proposed so far.

On local prediction based reversible watermarking.

The use of local prediction in difference expansion reversible watermarking provides very good results, but at the cost of computing for each pixel a least square predictor in a square block centered on the pixel. This correspondence investigates the reduction of the mathematical complexity by computing distinct predictors not for pixels, but for groups of pixels. The same predictors are recovered at detection. Experimental results for the case of prediction on the rhombus defined by the four horizontal and vertical neighbors are provided. It is shown that by computing a predictor for a pair of pixels, the computational cost is halved without any loss in performance. A small loss appears for groups of three and four pixels with the advantage of reducing the mathematical complexity to a third and a fourth, respectively.

Local-prediction-based difference expansion reversible watermarking.

This paper investigates the use of local prediction in difference expansion reversible watermarking. For each pixel, a least square predictor is computed on a square block centered on the pixel and the corresponding prediction error is expanded. The same predictor is recovered at detection without any additional information. The proposed local prediction is general and it applies regardless of the predictor order or the prediction context. For the particular cases of least square predictors with the same context as the median edge detector, gradient-adjusted predictor or the simple rhombus neighborhood, the local prediction-based reversible watermarking clearly outperforms the state-of-the-art schemes based on the classical counterparts. Experimental results are provided.