SPACE COMPLEXITY AND CLARITY ANALYSIS OF THUMBNAILATOR, MARVIN AND GRAPHIC 2DIMENSIONAL ALGORITHMS /
JONATHAN CHINEDU AKOBUNDU; SUPERVISOR: ASSOC. PROF. DR. TOLGAY KARANFİLLER
- xi, 69 sheets; 31 cm. Includes CD
Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Information Technologies Department
Includes bibliography (sheets 57-66)
ABSTRACT Image resizing techniques are used to alter an image's proportions while retaining as much of its visual information as feasible. The complexity analysis of different picture resizing methods relies on the methodology employed. I'll go over the complexity analysis for three popular picture scaling techniques in this section. These complexity evaluations are basic recommendations, and they might change depending on how certain algorithms are implemented and optimized. Additionally, a number of variables, such as software optimizations, picture size, and hardware capabilities, might affect an algorithm's real runtime speed. The study on the complexity of an algorithm have great impact on the whole fields of computer science and digital image processing. This study used Punia et al (2020) formula in calculating the space complexity and simulation technique in clarity parameter analysis of Thumbnailator, Marvin and Graphic 2Dimension algorithms to see which one among the algorithms consumed less and more space after scaling in computer memory as well as clarity maintenance in JAVA. Results from simulation analysis shows that Thumbnailator is the best algorithm as it maintained the quality of the image and has the minimum size compared to other algorithm, it also take half the size of the resize as other algorithm or followed by graphics 2D second to Thumbnailator but Marvin is not far worse than algorithm but it takes higher size but with good quality than graphics 2D. Keywords: Benchmaring, Electronic Code Book, Format Preserving, Performance, Rijandael, Rivest Cipher