# reprocessing steps for images before training classification models

I have a data set of images for classification task.

I read some articles about image reprocessing (before training CNN models) which summarize in those steps:

1. scale image values (img / 255.0)

2. remove noise (using Gaussian blur)

3. morphology

I'm not sure when to use each step and what is the right order of those steps:

1. Do we need to remove noise before scaling images ? (or it dosn't matter) ?

2. I didn't found many articals about morphology step:

2.1 When will we use morphology ? (Is it always right to use this reprocessing step ?

2.2 What is the right order ? use morphology after scaling and removing noise ?

1. Divided the image with 255.0 value is a normalization technic called min/max normalization. Like the other normalization methods, min/max normalization used to improve performance of CNN's.