Wavelet-based Image Denoising

Käesolev töö uurib laineteisenduste kasutust piltide kvaliteedi parandamise eesmärgil, neilt müra eemaldades. See annab ülevaate erinevates müra tüüpidest ning müraeemaldusmeetoditest. Edasi keskendub töö laineteisenduspõhistele müraeemaldusskeemidele. Samuti uurib töö laineteisenduspõhise müraeemaldusmeetodi ning kokkupakkimise kombineerimise kasulikkust ja pakub välja uue lävendamise tüübi ning muudatuse eksisteerivale BayesShrink meetodile. Pakutud meetod implementeeritakse C# keeles ning selle implementatsiooni tulemusi, jõudlust ning optimaalseid parameetreid analüüsitakse eksperimentaalsete tulemuste abil.This thesis studies the use of wavelets for the purpose of improving the quality of images by removing noise from them. It presents an overview of different types of noise and denoising methods. The thesis then focuses on the wavelet transform based denoising schemes. It explores the potential of combining wavelet-based denoising and compression, and presents a new thresholding type and a modification to the existing BayesShrink method. The proposed method is implemented in the C# language and its performance and optimal parameters are analyzed through experimental results

A flexible hardware architecture for 2-D discrete wavelet transform: design and FPGA implementation

The Discrete Wavelet Transform (DWT) is a powerful signal processing tool that has recently gained widespread acceptance in the field of digital image processing. The multiresolution analysis provided by the DWT addresses the shortcomings of the Fourier Transform and its derivatives. The DWT has proven useful in the area of image compression where it replaces the Discrete Cosine Transform (DCT) in new JPEG2000 and MPEG4 image and video compression standards. The Cohen-Daubechies-Feauveau (CDF) 5/3 and CDF 9/7 DWTs are used for reversible lossless and irreversible lossy compression encoders in the JPEG2000 standard respectively. The design and implementation of a flexible hardware architecture for the 2-D DWT is presented in this thesis. This architecture can be configured to perform both the forward and inverse DWT for any DWTfamily, using fixed-point arithmetic and no auxiliary memory. The Lifting Scheme method is used to perform the DWT instead of the less efficient convolution-based methods. The DWT core is modeled using MATLAB and highly parameterized VHDL. The VHDL model is synthesized to a Xilinx FPGA to prove hardware functionality. The CDF 5/3 and CDF 9/7 versions of the DWT are both modeled and used as comparisons throughout this thesis. The DWT core is used in conjunction with a very simple image denoising module to demonstrate the potential of the DWT core to perform image processing techniques. The CDF 5/3 hardware produces identical results to its theoretical MATLAB model. The fixed point CDF 9/7 deviates very slightly from its floating-point MATLAB model with a ~59dB PSNR deviation for nine levels of DWT decomposition. The execution time for performing both DWTs is nearly identical at -14 clock cycles per image pixel for one level of DWT decomposition. The hardware area generated for the CDF 5/3 is -16,000 gates using only 5% of the Xilinx FPGA hardware area, 2.185 MHz maximum clock speed and 24 mW power consumption. The simple wavelet image denoising techniques resulted in cleaned images up to -27 PSNR

Kajian motivasi ekstrinsik di antara Pelajar Lepasan Sijil dan Diploma Politeknik Jabatan Kejuruteraan Awam KUiTTHO

Kajian ini dijalankan untuk menyelidiki pengaruh dorongan keluarga, cara pengajaran pensyarah, pengaruh rakan sebaya dan kemudahan infrastruktur terhadap motivasi ekstrinsik bagi pelajar tahun tiga dan tahun empat lepasan sijil dan diploma politeknik Jabatan Kejuruteraan Awain Kolej Universiti Teknologi Tun Hussein Onn. Sampel kajian ini beijumlah 87 orang bagi pelajar lepasan sijil politeknik dan 38 orang bagi lepasan diploma politeknik. Data kajian telah diperolehi melalui borang soal selidik dan telah dianalisis menggunakan perisian SPSS (Statical Package For Sciences). Hasil kajian telah dipersembahkan dalam bentuk jadual dan histohgrapi. Analisis kajian mendapati bahawa kedua-dua kumpulan setuju bahawa faktor-faktor di atas memberi kesan kepada motivasi ekstrinsik mereka. Dengan kata lain faktpr-faktor tersebut penting dalam membentuk pelajar mencapai kecemerlangan akademik