Underwater image enhancement using DCP with ACCLAHE and homomorphism filtering

Image enhancement (IE) methods present as a preprocessing step in object detection and recognition in computer vision applications. The excellence of underwater images is negative in view that of precise propagation residences of light in water. So, underwater image enhancement is crucial to increase visual pleasant. In this research, presented an underwater IE using dark channel prior (DCP) with adaptively clipped contrast limited histogram equalization (ACCLAHE) and homomorphism filtering (HF). Using DCP, estimate blur region and remove them. With the help of ACCLAHE, it takes the maximum bin height in the local histogram of the sub-image and redistributes the clipped pixels equally to each gray-level. HF is used for improving the edges of an image.