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Yayın Wavelet based image coding and interpolation(Işık Üniversitesi, 2009) Tamer, Engin; Ateş, Hasan Fehmi; Işık Üniversitesi, Fen Bilimleri Enstitüsü, Elektronik Mühendisliği Yüksek Lisans ProgramıThe need of higher resolution on imaging systems and displays increases everyday. Data rates and bandwidth are still limited to satisfy the demands of enhanced resolutions. So, we should develop intelligent enhancement tools which yield higher resolution images with comparably limited bitrate. In this thesis, we examine the quality enhancement capabilities of two di erent approaches, i.e. image coding and image interpolation. Better image coding algorithms are capable of producing enhanced higher detail images at the same bitrate. For that purpose, we design an e cient and intelligent wavelet based image coding algorithm that codes the hierarchical description of wavelet coe cients instead of coding themselves. Namely, we introduce the hierarchical quantization index tree which is composed of quantization index classes. These index classes are constructed using combination of similar wavelet coe cients which leads an adaptive structure. Then, this hierarchical tree is optimized by a simple rate-distortion analysis to achieve e cient bit allocation among various di erent regions of natural images. In the second part of the thesis, we propose a wavelet based interpolation algorithm that exploits the correlation between high resolution(HR) and low resolution(LR) images. Basically, we design linear minimum mean square error lters between HR and LR images to recover lost high frequency information. For modeling the relationship between two resolutions, we use two di erent approaches, i.e. block based lter design and context adaptive lter design. In block based lter design algorithm, we partition the image into blocks to capture local frequency variations. In context adaptive algorithm, we use a simple context to adapt di erent image structures. We also brie y mention how these new approaches can be integrated into a novel coding + resolution enhancement joint framework. Simulations show that both our coding and interpolation algorithms perform better than most existing schemes.
