Noise Estimation and Type Identification in Natural Scene and Medical Images using Deep Learning Approaches

Algorithm 2

Proposed algorithm for noise type identification.

Input: Noised images

Output: Identified noise type

Method:

Step 1: Read images

    For i = 1 to n do

       Read image I_i

       Repeat step 2–5 for each image

Step 2: Resize an image

       Resize image I_i to 256 × 256

Step 3: DWT transformation

       [LL, LH,HL,HH] = DWT transformation.

Step 4: Edge Detection and reduce size to match with HH sub-band

       I_d = Detect edges of I_i using the Sobel operator.

       I_dd = Downsample the image by two rows and two columns.

Step 5: Remove edge component from HH sub-band

       I_we = HH ○ I_dd Hadamard operation

Step 6: Train and test the CNN model using the images obtained in step 5

    Divide images in the ratio 60 : 20 : 20.

Step 7: Measure the performance.