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Improving the Contrast of Aerial Images using a New Multi-concept Algorithm
Zohair Al-Ameen 대한전자공학회 2020 IEIE Transactions on Smart Processing & Computing Vol.9 No.5
Aerial images are highly beneficial for a range of real-life applications. On the other hand, the quality of these images is often degraded by a low-contrast effect caused by many causatives that are difficult to avoid during the acquisition process. Therefore, a new multi-concept algorithm is proposed to improve the contrast of aerial images adequately in a fully automatic way. The proposed algorithm combines several processing concepts of S-curve mapping functions, logarithmic image processing, and normalization. The newly developed algorithm was tested with artificial and natural-degraded images, and the quality of the resulting images from different comparisons was evaluated using four advanced image quality assessment (IQA) metrics. Intensive experiments and evaluations showed that the proposed algorithm could improve the contrast for various types of aerial images rapidly. In addition, it could outperform many advanced contrast enhancement algorithms regarding the IQA scores, perceived quality, and processing speed.
Zohair Al-Ameen,Ghazali Sulong 보안공학연구지원센터 2016 International Journal of Grid and Distributed Comp Vol.9 No.10
Computed Tomography (CT) has remained an important component of medical imaging since its inception. In general, it is preferred to keep the radiation dose as low as possible during the CT examinations to prevent patients as well as operators from the dangerous side effects of these radiations, which in an extreme case may lead to cancer. However, reducing the radiation dose leads to undesirable degradations which not only reduce the visual quality of CT images, but also make such images difficult to interpret in clinical routines. The most common degradations in low-dose CT images include blur, noise and low-contrast. Over the recent years, considerable research has been made to process these degradations. However, they still remain open for research due to the wide variety of challenges they offer. In this article, the causing factors of such degradations are addressed adequately. Furthermore, the challenges that face the processing of these degradations are mentioned in detail. Finally, this article is intended for researchers who are approaching this topic to understand the aforesaid issues extensively.
Zohair Al-Ameen,Ghazali Sulong 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.7
Magnetic Resonance (MR) images provide physicians with vital information about different diseases of the human body. Thus, such images must have adequate clarity to become highly beneficial in the medical field. However, it is known that MR images have a poor dynamic range which significantly affects their visible quality due to the deficient brightness and contrast. In order to deliver evident results, a tuned single-scale Retinex algorithm is utilized in this study to ameliorate the dynamic range which eventually results in better brightness and contrast. The obtained results are compared with various algorithms that utilize contemporary, complex and renowned concepts. Moreover, many naturally-degraded MR images are used for experimental and comparable purposes. Finally, intensive experiments revealed the favorability of the adopted algorithm, in that it produced evident results without any visible flaws and outperformed the comparable algorithms in terms of visible quality.