000			02233nam a22001817a 4500
003			FT8922
005			20260107132238.0
050			_aQA76.9 A43 C37 2025
100	1		_aCastro, Rona Jean B.; Sanchez, Niño Angelo A.
245			_aEnhancement of discrete wavelet transform algorithm applied in medical image compression
264		1	_cc2025
300			_bUndergraduate Thesis: (Bachelor of Science in Computer Science) - Pamantasan ng Lungsod ng Maynila, 2025
336			_2text _atext _btext
337			_2unmediated _aunmediated _bunmediated
338			_2volume _avolume _bvolume
505			_aABSTRACT: The Discrete Wavelet Transform (DWT) is a widely used technique in medical image compression due to its ability to capture both spatial and frequency characteristics of images. However, traditional DWT suffers from several limitations, including the lack of phase information, shift variance, and limited directional selectivity, which can lead to distortions, misaligned edges, and loss of critical details in reconstructed medical images. This study proposes an enhanced DWT algorithm that addresses these limitations by integrating a trained Autoencoder for phase information preservation, implementing the Stationary Wavelet Transform (SWT) to mitigate shift variance, and employing a Directional Filter Bank (DFB) to improve directional selectivity. The proposed framework is evaluated using medical image datasets, including MRI, CT scans, and X-rays, with performance metrics such as Peak Signal-to-Noise Ratio (PSNR), Mean Reconstruction Error (MRE), and Coefficient Differences, Results demonstrate significant improvements in image quality, edge preservation, and compression efficiency, with up to 61.90% improvement in PSNR and reduced reconstruction error compared to traditional DWT. The enhanced algorithm ensures that critical diagnostic details are preserved, making it suitable for applications in medical imaging where accuracy and efficiency are paramount. This study contributes to the advancement of wavelet-based compression techniques, providing a robust solution for maintaining the integrity and diagnostic quality of medical images while reducing storage and bandwidth requirements.
942			_2lcc _cMS
999			_c37402 _d37402