Generally speaking you have two class A (infected) and B (not infected). All entropy measures will indicate more ordered states with lower values and disordered with higher. From data (images) described with appropriate parameters (features) at disposal classification entropy threshold value can be detected which is on the other hand is not an easy task - some good heuristic or expert knowledge should be used. 

Thanks for your answer.

Dear Malarvel , my view points here given as follows :

1. First of all Entropy means : Amount of redundant information  (amount of information contains in image)

2.I hope your application is classification of  infected and  not infected , so you may try any classification tool like neural network or any modified classifiers

3 In case of Classification , role of Entropy is as the one training parameter 

4. But If you want to concentrate only in Entropy then you suppose to do training with many sample images [ both infected and not infected] 

5. If you use more parameters accuracy will increase 

I hope it will helps you , for future any queries [email protected]