human: Given a node-centered hypergraph: <hypergraph>, where nodes represent authors and hyperedges represent groups of authors who co-authored the same paper.

Details of the hypergraph:
Center node: "A reversible data hiding method with contrast enhancement for medical images"
  Abstract: Reversible data hiding with contrast enhancement is performed on medical images.Pre-processing is improved so that better visual quality can be obtained.Principal values in background are differentiated to improve image quality.Better contrast enhancement effects than the previous work are achieved. In this paper, a reversible data hiding method with contrast enhancement is presented for medical images. Firstly, image background segmentation is performed and the principal gray-scale values in the segmented background are identified. By excluding the corresponding histogram bins from being expanded for data hiding, the contrast of region of interest (ROI) in medical images can be selectively enhanced. Considering the characteristics of pixel distribution, we develop a new pre-processing strategy to reduce the visual distortions that may be caused. With the proposed method, an original image can be exactly recovered from the corresponding enhanced image by hiding the side information within it. The experimental results on a set of medical images show that the visibility of ROI can be improved. Compared with the previous method, the proposed method can achieve more contrast enhancement effects and better visual quality for medical images.

Connected through hyperedge HE-1 (induced by source paper "Reversible data hiding"):
  with members:
    - "Secure spread spectrum watermarking for multimedia"

Question: Please tell me which research area the center author belongs to. The 4 classes are: Computer science, Mathematics, Engineering, Economics, Psychology, Business. Directly output the class name.

gpt: Computer science