human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the ihs transformations based image fusion"
  Abstract: The IHS sharpening technique is one of the most commonly used techniques for sharpening. Different transformations have been developed to transfer a color image from the RGB space to the IHS space. Through literature, it appears that, various scientists proposed alternative IHS transformations and many papers have reported good results whereas others show bad ones as will as not those obtained which the formula of IHS transformation were used. In addition to that, many papers show different formulas of transformation matrix such as IHS transformation. This leads to confusion what is the exact formula of the IHS transformation?. Therefore, the main purpose of this work is to explore different IHS transformation techniques and experiment it as IHS based image fusion. The image fusion performance was evaluated, in this study, using various methods to estimate the quality and degree of information improvement of a fused image quantitatively.

Connected through hyperedge HE-1 (induced by source paper "major limitations of satellite images"):
  with members:
    - "a novel metric approach evaluation for the spatial enhancement of pan sharpened images"
    - "spatial and spectral quality evaluation based on edges regions of satellite image fusion"
    - "the statistical methods of pixel based image fusion techniques"
    - "arithmetic and frequency filtering methods of pixel based image fusion techniques"

Connected through hyperedge HE-2 (induced by source paper "image fusion technologies in commercial remote sensing packages"):
  with members:
    - "a novel metric approach evaluation for the spatial enhancement of pan sharpened images"
    - "spatial and spectral quality evaluation based on edges regions of satellite image fusion"
    - "the statistical methods of pixel based image fusion techniques"

Connected through hyperedge HE-3 (induced by source paper "spatial and spectral quality evaluation based on edges regions of satellite image fusion"):
  with members:
    - "the statistical methods of pixel based image fusion techniques"
    - "studying satellite image quality based on the fusion techniques"
    - "arithmetic and frequency filtering methods of pixel based image fusion techniques"
    - "multisensor images fusion based on feature level"

Connected through hyperedge HE-4 (induced by source paper "a novel metric approach evaluation for the spatial enhancement of pan sharpened images"):
  with members:
    - "the statistical methods of pixel based image fusion techniques"
    - "arithmetic and frequency filtering methods of pixel based image fusion techniques"
    - "multisensor images fusion based on feature level"

Connected through hyperedge HE-5 (induced by source paper "studying satellite image quality based on the fusion techniques"):
  with members:
    - "the statistical methods of pixel based image fusion techniques"
    - "arithmetic and frequency filtering methods of pixel based image fusion techniques"
    - "multisensor images fusion based on feature level"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CV(Computer Vision and Pattern Recognition)