Evaluation of various digital image processing techniques for detecting critical crescent moon and introducing CMD – A tool for critical crescent moon detection

• Published in: Optik (Stuttgart) Vol. 127; no. 3; pp. 1511 - 1525
• Main Authors: Hashemi Sejzei, Akram, Jamzad, Mansur
• Format: Journal Article
• Language: English
• Published: Elsevier GmbH 01.02.2016
• Subjects: Astronomical image processing; CCD camera; Crescent moon detection; Image enhancement; Image processing; HShistV; Image processing; CCD; CLAHE; Astronomical image processing; Crescent moon detection; MSR; FSSR; CurvHShistV; PB; SSR; CCD camera; HGSNI; POSP; CMD; POSHE; Image enhancement; MSRCR
• ISSN: 0030-4026; 1618-1336
• DOI: 10.1016/j.ijleo.2015.09.158

Critical crescent moon detection is a new subject in astronomical image processing. Astronomers take photos with valuable astronomical calculations using CCD cameras and telescopes. Crescent moon might not be visible in such photos, so they must be enhanced. For this purpose, we apply common image processing methods on crescent moon images such as power operator, gamma transformation, global and local histogram equalization, POSHE, CLAHE, local enhancement, gain/offset correction, homomorphic filtering, SSR, MSR, MSRCR, wavelet and curvelet transformations. Second, we use our new methods like PB, POSP, HShistV, CurvHShistV and local brightness intensity enhancement to detect the crescent. Then we evaluate and compare the outputs of these algorithms by standard subjective evaluation tests. Finally, we conclude that these methods can give us enhanced images in which the crescent moon can be seen by human observers. We introduce our new toolbox which is named CMD, a standalone tool developed in Matlab for Critical Crescent Moon Detection using the above techniques.