Fast Dust Sand Image Enhancement Based on Color Correction and New
  Membership Function
Ali Hakem Alsaeedi Suha Mohammed Hadi Yarub Alazzawi
Images captured in dusty environments suffering from poor visibility and
quality. Enhancement of these images such as sand dust images plays a critical
role in various atmospheric optics applications. In this work, proposed a new
model based on Color Correction and new membership function to enhance san dust
images. The proposed model consists of three phases: correction of color shift,
removal of haze, and enhancement of contrast and brightness. The color shift is
corrected using a new membership function to adjust the values of U and V in
the YUV color space. The Adaptive Dark Channel Prior (A-DCP) is used for haze
removal. The stretching contrast and improving image brightness are based on
Contrast Limited Adaptive Histogram Equalization (CLAHE). The proposed model
tests and evaluates through many real sand dust images. The experimental
results show that the proposed solution is outperformed the current studies in
terms of effectively removing the red and yellow cast and provides high quality
and quantity dust images.