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Images captured in dusty environments suffering from poor visibility andquality. Enhancement of these images such as sand dust images plays a criticalrole in various atmospheric optics applications. In this work, proposed a newmodel based on Color Correction and new membership function to enhance san dustimages. The proposed model consists of three phases: correction of color shift,removal of haze, and enhancement of contrast and brightness. The color shift iscorrected using a new membership function to adjust the values of U and V inthe YUV color space. The Adaptive Dark Channel Prior (A-DCP) is used for hazeremoval. The stretching contrast and improving image brightness are based onContrast Limited Adaptive Histogram Equalization (CLAHE). The proposed modeltests and evaluates through many real sand dust images. The experimentalresults show that the proposed solution is outperformed the current studies interms of effectively removing the red and yellow cast and provides high qualityand quantity dust images.

Fast Dust Sand Image Enhancement Based on Color Correction and New Membership Function