NO-REFERENCE QUALITY ASSESSMENT OF MEDICAL IMAGES USING CONTRAST ENHANCEMENT
Omarova G. Starovoitov V. Myrzamuratova A. Akzullakyzy L. Takuadina A. Tanirbergenov A. Beisenbayeva K. Sadirmekova Z.
15 January 2023Little Lion Scientific
Journal of Theoretical and Applied Information Technology
2023#101Issue 1267 - 281 pp.
Contrast distortion is often a determining factor in human perception of image quality, but little investigation has been dedicated to quality assessment of contrast-distorted images without assuming the availability of a perfect-quality reference image. In many real-world applications, images are prone to be degraded by contrast distortions during image acquisition. Quality assessment for contrast-distorted images is vital for benchmarking and optimizing the contrast-enhancement algorithms. Visual study of medical images is essential for the diagnosis of many diseases. Various contrast enhancement methods such as histogram equalization, histogram modification methods, gamma correction, etc. are used to improve the contrast of medical images. Image quality evaluation is an integral part of the contrast enhancement and image enhancement processes. Quantitative measures of digital image quality make it possible to compare the applied processing methods and choose the best of them. The article studied methods for improving the quality of x-rays. The research was carried out in several stages. Attempts were made to increase the contrast of several tens of X-ray images in order to select the best image brightness using brightness transformation methods in the MATLAB system. Contrast improvement is supported by objective scores calculated by the NIQE and BRISQUE functions that do not require reference images. As a result of successive experiments, recommendations were proposed for selecting the parameters of the gamma correction method and the adaptive histogram equalization method, where contrast enhancement is limited in order to avoid the appearance or enhancement of noise in the image. The experiment is based on the algorithms of objective non-reference quality assessment NIQE and BRISQUE. A feature of this work is the use of objective non-reference estimates to determine the quality of images. The performed experiments allow to give preference to the NIQE assessment, since it corresponded to the results of image contrast enhancement.
Contrast Enhancement , Digital X-Ray Image , Image Enhancement , Image Quality Evaluation
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L. N. Gumilyov Eurasian National University, Astana, Kazakhstan
United Institute of Informatics Problems, The National Academy of Sciences of Belarus, Minsk, Belarus
Korkyt Ata Kyzylorda University, Kyzylorda, Kazakhstan
Karaganda Medical University, Karaganda, Kazakhstan
Taraz Regional University named after M.KH. Dulaty, Taraz, Kazakhstan
L. N. Gumilyov Eurasian National University
United Institute of Informatics Problems
Korkyt Ata Kyzylorda University
Karaganda Medical University
Taraz Regional University named after M.KH. Dulaty
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