Underwater images suffer from blurring effects, low contrast, and grayed out colors due to
the absorption and scattering effects under the water. Many image enhancement algorithms …

Quality evaluation of underwater images is a key goal of underwater video image retrieval
and intelligent processing. To date, no metric has been proposed for underwater color …

Many applications of histograms for the purposes of image processing are well known.
However, applying this process to the transform domain by way of a transform coefficient …

No-reference (NR) image quality assessment is essential in evaluating the performance of
image enhancement and retrieval algorithms. Much effort has been made in recent years to …

Varying scene illumination poses many challenging problems for machine vision systems.
One such issue is developing global enhancement methods that work effectively across the …

The goal of contrast enhancement is to improve visibility of image details without introducing
unrealistic visual appearances and/or unwanted artefacts. While global contrast …

Underwater images, which have low contrast and visibility as a result of selective attenuation
based on the wavelength of the light passing through water, needs some corrections to …

Image processing technologies such as image enhancement generally utilize linear
arithmetic operations to manipulate images. Recently, Jourlin and Pinoli successfully used …

Contrast and color are important attributes to extract and acquire much information from
underwater images. However, normal underwater images contain bright foreground and …

Evaluation of images, after processing, is an important step for determining how well the
images are being processed. Quality of image is usually assessed using image quality …