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: "arithmetic and frequency filtering methods of pixel based image fusion techniques"
  Abstract: In remote sensing, image fusion technique is a useful tool used to fuse high spatial resolution panchromatic images (PAN) with lower spatial resolution multispectral images (MS) to create a high spatial resolution multispectral of image fusion (F) while preserving the spectral information in the multispectral image (MS).There are many PAN sharpening techniques or Pixel-Based image fusion techniques that have been developed to try to enhance the spatial resolution and the spectral property preservation of the MS. This paper attempts to undertake the study of image fusion, by using two types of pixel –based image fusion techniques i.e. Arithmetic Combination and Frequency Filtering Methods of Pixel-Based Image Fusion Techniques. The first type includes Brovey Transform (BT), Color Normalized Transformation (CN) and Multiplicative Method (MLT). The second type include High-Pass Filter Additive Method (HPFA), High – Frequency- Addition Method (HFA) High Frequency Modulation Method (HFM) and The Wavelet transformbased fusion method (WT). 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), EntropyሺEn ), 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 statistical methods of pixel based image fusion techniques"
    - "the ihs transformations based image fusion"

Connected through hyperedge HE-2 (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"
    - "the ihs transformations based image fusion"
    - "multisensor images fusion based on feature level"

Connected through hyperedge HE-3 (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"
    - "the ihs transformations based image fusion"
    - "multisensor images fusion based on feature level"

Connected through hyperedge HE-4 (induced by source paper "studying satellite image quality based on the fusion techniques"):
  with members:
    - "the statistical methods of pixel based image fusion techniques"
    - "the ihs transformations based image fusion"
    - "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)