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

Claim 4:
5. The method of claim 1, wherein performing Bayesian denoising on noisy images based on the distribution constraint of noiseless images comprises:
constructing a Bayesian posterior cost function Ψ for the noisy image samples z1, z2, z3, . . . , zn and the estimated noiseless image samples ŝ1, ŝ2, ŝ3, . . . , ŝn, ψ
   ⁡
   (
   
    
     
      s
      ˆ
     
     1
    
    ,
    
     
      s
      ˆ
     
     2
    
    ,
    
     
      s
      ˆ
     
     3
    
    ,
    …
        
    ,
    
     
      s
      ˆ
     
     n
    
   
   )
  
  =
  
   
    
     ∑
     
      i
      =
      
       1
       :
       n
      
     
    
    
     
      φ
      f
     
     (
     
      
       z
       i
      
      -
      
       
        s
        ˆ
       
       i
      
     
     )
    
   
   +
   
    λ
    ⁢
    D
   
  
 

where, the first term ϕf of the Bayesian posterior cost function Ψ is a data fidelity term between the noisy image samples z1, z2, z3, . . . , zn and the estimated noiseless image samples ŝ1, ŝ2, ŝ3, . . . , ŝn, the second term D is the distribution constraint, that is, distribution distance D(Ŝ,S) or the distribution distance D({circumflex over (Z)},Z), λ is a hyperparameter adjusting the importance of the distribution constraint; and
minimizing the Bayesian posterior cost function Ψ and obtaining final estimated noiseless images ŝ1, ŝ2, ŝ3, . . . , ŝn.