Abstract

The selection of texture information and block ringing effect in multi-focus fusion process, a new multi-focus image fusion algorithm based on Three Activity Measures (TAM) excitation Spiking Cortical Model, (SCM) in shearlet (SHT) domain is proposed. Firstly, in SHT domain, using local spatial frequency (SF), local energy of gradient (EOG) and different measurements (SF, EOG, and local laplace energy sum (SML)) motivated SCM selected the texture information and construct the initial fusion image (P). Then, the focal region was extracted from the significant feature of the difference between the image P and the original image. Finally, the joint focus area produces fusion images. To verify the superiority of the proposed algorithm, compare the results of this paper with seven competing methods. Experimental results show that the algorithm can produce clear edges, good visual perception and less distortion.

Highlights

  • SHT 变换Ψa,s,t( x) 函数来构造。 Ψ ∈ L2(R2) 满足以下条件:对于任何 ξ = (ξ1, ξ2) ∈ R^ 2( ξ2 ≠ 0) , 我们假设Ψ^ ( ε1,ε2) = Ψ^ 1( ε1) Ψ^ 2( ε2 / ε1) ,其中 Ψ^ ( ε) 表示 Ψ( ε) 的傅里 叶变换,Ψ1 是连续小波。 Ψ^ 1 ∈ C∞ ( R) ,suppΨ1 ⊂ [ - 2, - 1 / 2] ∪ [1 / 2,2] 。 Ψ^ 2 ∈ C∞ ( R) ,suppΨ2 ⊂ [ - 2, - 1 / 2] ∪ [1 / 2,2] ,其中,Ψ^ 2 ≥ 0 并且 ‖Ψ2‖ = 1。 我们假设: 利用 Ψ^ 1 和 Ψ^ 2 所支撑得条件,函数 Ψj,l,k 所具有 的频率支撑给出如下: suppΨ^ (j,0l,)k ⊂ { ( ξ1 ,ξ2 ) :ξ1 ∈ [ - 22j-1 , - 22j-4 ] ∪ ≤ 1} , 有如下方程: A0j x k) :

  • Fusion Technique for Multi⁃Focus Images Based on NSCT⁃ISCM[ J]

  • Image Fusion Algorithm of Focal Region Detection and TAM⁃SCM Based on SHT Domain

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Summary

SHT 变换

Ψa,s,t( x) 函数来构造。 Ψ ∈ L2(R2) 满足以下条件:对于任何 ξ = (ξ1, ξ2) ∈ R^ 2( ξ2 ≠ 0) , 我们假设Ψ^ ( ε1,ε2) = Ψ^ 1( ε1) Ψ^ 2( ε2 / ε1) ,其中 Ψ^ ( ε) 表示 Ψ( ε) 的傅里 叶变换,Ψ1 是连续小波。 Ψ^ 1 ∈ C∞ ( R) ,suppΨ1 ⊂ [ - 2, - 1 / 2] ∪ [1 / 2,2] 。 Ψ^ 2 ∈ C∞ ( R) ,suppΨ2 ⊂ [ - 2, - 1 / 2] ∪ [1 / 2,2] ,其中,Ψ^ 2 ≥ 0 并且 ‖Ψ2‖ = 1。 我们假设: 利用 Ψ^ 1 和 Ψ^ 2 所支撑得条件,函数 Ψj,l,k 所具有 的频率支撑给出如下: suppΨ^ (j,0l,)k ⊂ { ( ξ1 ,ξ2 ) :ξ1 ∈ [ - 22j-1 , - 22j-4 ] ∪ ≤ 1} , 有如下方程: A0j x k) :

SCM 的数学模型
SHT 域的多聚焦图像融合
Objective
Full Text
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