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Haze Elimination Model-Based Color Saturation Adjustment With Contrast Correction

Reman Kumar, Ashish Kumar Bhandari, Manish Kumar

2022IEEE Transactions on Instrumentation and Measurement16 citationsDOI

Abstract

In this paper, an effective contrast enhancement algorithm has been proposed to enhance the contrast of an image with preserved color details and visually similar to the undistorted reference image. The proposed algorithm is divided into two parts such as color saturation enhancement and brightness enhancement. The haze removal approach using the atmospheric scattering model is used to formulate a color saturation enhancement function for the low contrast image. The haze removal approach using the scattering model degrades the brightness in the output image. The brightness of the enhanced output using the haze removal model is restored using the proposed enhancement function, which maintains the natural brightness of the input image. The proposed algorithm manages to preserve the natural appearance and brightness of the image using the brightness function. The average computation time for the proposed method is very low and is suitable for real-time applications. The proposed method is evaluated over some of the popular image quality evaluation matrices on the images of the standard datasets. The qualitative, quantitative, and statistical analysis reflects that the proposed algorithm consistently enhances the low contrast images with preserved color and natural appearance.

Topics & Concepts

BrightnessHazeArtificial intelligenceComputationContrast (vision)Computer visionComputer scienceImage restorationSaturation (graph theory)Gamma correctionImage qualityImage (mathematics)AlgorithmMathematicsOpticsImage processingPhysicsMeteorologyCombinatoricsImage Enhancement TechniquesAdvanced Image Fusion TechniquesImage and Video Quality Assessment
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