Adaptive Histogram Equalization based Approach for SAR Image Enhancement: A Comparative analysis

Nowadays, flood is the most frequently occurring natural disaster among all-natural disasters. A flood is a disaster that causes huge causalities. Recovery from these huge causalities is a very serious concern for developing countries. This research work focuses on flush food, which is a very common disaster that occurs due to heavy rainfall or some manmade reasons. An Image of the flooded area provides useful information for taking necessary precautions in that particular situation. If the captured image is of poor quality, then isn't provide sufficient information. This paper considers the Synthetic Aperture Radar (SAR) images of the flooded area and it is mainly focused on increasing the image's visual quality. There are various image enhancement techniques available; this paper has used the histogram-based image quality improvement technique done by the Histogram Equalization (HE) method. To defeat the limitation of HE, another enhancement approach named Adaptive Histogram Equalization (AHE) is also used. In many cases, HE is increasing the quality of the image, but on the other side over brightness is causes the loss of some useful background information. In the AHE technique, the image is divided into small blocks: an equalization function is applied on each block. Both the techniques are compared on the various images of the flooded area, and the result shows that AHE provides better results.