Abstract:

The exploration of the underwater world has become an intriguing research subject in recent years. However, factors such as blurriness, color distribution, and contrast in the underwater environment lead to distortions such as noise and loss of detail in underwater images. This situation increases the challenges encountered in underwater image analysis applications. Image enhancement algorithms can be employed to overcome these problems. The aim of this study is to improve underwater images using existing image enhancement algorithms. Single Scale Retinex (SSR), Multi Scale Retinex (MSR), Multi Scale Retinex with Color Restoration (MSRCR), Dehazing Histogram Distribution Prior (DHDP), and Multi-Scale Correlated Wavelet (MSCW) are among the enhancement algorithms used in this study. This study was applied to images selected from a data set containing real-world data. Evaluations with both full-reference and no-reference metrics were conducted to demonstrate the enhancement algorithms' performance. According to the results obtained from the evaluation metrics of the selected images, images enhanced with the MSRCR algorithm generally achieved better results on average. The average scores for the MSRCR algorithm in Peak Signal-to-Noise Ratio, Structural Similarity Index, Blind/referenceless Image Spatial Quality Evaluator, Naturalness Image Quality Evaluator, Perception based Image Quality Evaluator, Underwater Image Quality Measure, and Underwater Color Image Quality Evaluation, underwater image quality criterion, and underwater colored image quality evaluation criteria are 15.6454, 0.4516, 22.6035, 6.4106, 34.7032, 1.7344, and 7.776, respectively. Experimental results demonstrate the effectiveness of image enhancement methods in reducing distortions in underwater images.

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