Abstract
This study discusses strategies for identifying Diabetic Retinopathy (DR) using fundus images and the efficiency of image pre-processing techniques to improve their quality. Fundus images in medical image processing often experience problems with non-uniform lighting, low contrast, and noise, thus requiring pre-processing of images to improve their quality. This study evaluates the effectiveness of standard histogram equation techniques and optimized histogram equations with cukkoo optimization in order to choose the best technique to improve fundus image quality to identify DR. The proposed technique to produce better image quality improvements will be tested in several performance metrics, such as NIQE, PSNR, and Entropy. the results of this study, the average PNSR before optimization was 50,8, whereas after optimization it became 49,8239. The average entropy before optimization is 4.5514, while after optimization it becomes 3.8577. The average NIQE before optimization was 3,4046, while after optimization it was 4,73. In general, the results of this study indicate that the quality of the fundus image is better using the histogram equation before optimization than after optimization. In other words, Cukcoo optimization is not suitable for increasing the performance of the histogram equation in improving fundus image quality
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
