Patent ID: 11880903
Assignee: TSINGHUA UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 8:
9. The method of claim 1, wherein calculating a distribution distance D({circumflex over (Z)},Z) between a set {circumflex over (Z)} for the estimated noisy image samples {circumflex over (z)}1, {circumflex over (z)}2, {circumflex over (z)}3, . . . , {circumflex over (z)}n and a set Z for the noisy image samples z1, z2, z3, . . . , zn according to a distribution distance function D, comprises:
assuming that the distribution distance function D contains a neural network discriminator ΩD as a distribution distance operator, in which the neural network discriminator ΩD has a parameter set θD; and
using the distribution of the set {circumflex over (Z)} for estimated noisy image samples and the distribution of the set Z for real noisy image samples to compute distribution distance D({circumflex over (Z)},Z), where the distribution distance function D is defined by a cross entropy distance function, which is realized by the neural network discriminator ΩD:, D
   ⁡
   (
   
    
     Z
     ˆ
    
    ,
    Z
   
   )
  
  =
  
   
    
     ∑
     
      i
      =
      
       1
       :
       n
      
     
    
    
     log
     ⁡
     (
     
      
       Ω
       D
      
      (
      
       
        z
        i
       
       ;
       
        θ
        D
       
      
      )
     
     )
    
   
   +
   
    log
    ⁡
    (
    
     1
     -
     
      
       Ω
       D
      
      (
      
       
        
         z
         ˆ
        
        i
       
       ;
       
        θ
        D
       
      
      )
     
    
    )
   
  
 

or a Wasserstein distance function:, D
   ⁡
   (
   
    
     Z
     ˆ
    
    ,
    Z
   
   )
  
  =
  
   
    ∑
    
     i
     =
     
      1
      :
      n
     
    
   
   
    
     
      ❘
      "\[LeftBracketingBar]"
     
     
      
       
        Ω
        D
       
       (
       
        
         z
         i
        
        ;
        
         θ
         D
        
       
       )
      
      -
      
       
        Ω
        D
       
       (
       
        
         
          z
          ˆ
         
         i
        
        ;
        
         θ
         D
        
       
       )
      
     
     
      ❘
      "\[RightBracketingBar]"
     
    
    .