Computational Intelligence and Neuroscience

Research Article

[Retracted] An Efficient Stacked Deep Transfer Learning Model for Automated Diagnosis of Lyme Disease

Second-order edge-based color constancy algorithm.

	Begin
Input: Color image (C_I) having size M and N Minkowski’s norm (m_n) = 5 Sigma () = 2 differential order(d_o) = 2.
Step 1: Divide C_I into R_I, G_I, and B_I.
Step 2: Remove saturated color points. It represents those pixels that are greatly influenced by the light direction [21, 22].
Step 3Computed aggregated color values as [23]:



Here, , , and define the aggregated color values of , , and , respectively.
Step 4: Compute the average of all color channels as [24]:

Step 5: Computer the impact of color saturation as [25, 26]:



Step 6: Remove the color saturation as [18, 27]:



Step 7: Evaluate the effect illuminance () using 2^nd order edge-based approach as:

Step 8: Evaluate the impact of light on each color channel as [18, 28]:



Here, , , and show the mask containing the saturated pixels.
Step 9: Evaluate the aggregated impact of normalized whiteness in the color channels as [18, 29]:

Step 10: Compute the impact of light source as:



Step 11: Compute the restored color channels as



Step 12: Return concatenated (R_o, G_O, and B_o)