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 statistical methods of pixel based image fusion techniques"
  Abstract: There are many image fusion methods that can be used to produce high-resolution mutlispectral images from a high-resolution panchromatic (PAN) image and low-resolution multispectral (MS) of remote sensed images. This paper attempts to undertake the study of image fusion techniques with different Statistical techniques for image fusion as Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Regression variable substitution (RVS), Local Correlation Modeling (LCM) and they are compared with one another so as to choose the best technique, that can be applied on multi-resolution satellite images. This paper also devotes to concentrate on the analytical techniques for evaluating the quality of image fusion (F) by using various methods including Standard Deviation (SD), Entropy(En), Correlation Coefficient (CC), Signal-to Noise Ratio (SNR), Normalization Root Mean Square Error (NRMSE) and Deviation Index (DI) 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 ihs transformations based image fusion"
    - "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 ihs transformations based image fusion"

Connected through hyperedge HE-3 (induced by source paper "spatial and spectral quality evaluation based on edges regions of satellite image fusion"):
  with members:
    - "studying satellite image quality based on the fusion techniques"
    - "the ihs transformations based image fusion"
    - "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 ihs transformations based image fusion"
    - "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 ihs transformations based image fusion"
    - "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)