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 Decomposition Framework for Image Denoising Algorithms"
  Abstract: In this paper, we consider an image decomposition model that provides a novel framework for image denoising. The model computes the components of the image to be processed in a moving frame that encodes its local geometry (directions of gradients and level lines). Then, the strategy we develop is to denoise the components of the image in the moving frame in order to preserve its local geometry, which would have been more affected if processing the image directly. Experiments on a whole image database tested with several denoising methods show that this framework can provide better results than denoising the image directly, both in terms of Peak signal-to-noise ratio and Structural similarity index metrics.

Connected through hyperedge HE-1 (induced by source paper "A framework for objective image quality measures based on intuitionistic fuzzy sets"):
  with members:
    - "Ear recognition using local binary patterns: A comparative experimental study"

Connected through hyperedge HE-2 (induced by source paper "Is Denoising Dead"):
  with members:
    - "Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries"

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: Mathematics