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In the field of image processing, reference-free image quality assessment (IQA) algorithms are of great importance. These algorithms aim to evaluate the quality of an image without comparing it to a reference image. This is particularly useful in situations where a reference image is not available or when the image is degraded in a way that prevents the use of a reference image. However, developing an effective reference-free IQA algorithm is a complex task that requires a deep understanding of image processing techniques and statistical modeling. Therefore, researchers are constantly working to improve the accuracy and effectiveness of these algorithms.