3 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 3 / 3
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.Yayın Wavelet-based image compression by hierarchical quantization indexing(IEEE, 2009) Ateş, Hasan Fehmi; Tamer, EnginIn this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet coefficients. A hierarchical classification map is defined in each wavelet subband, which describes the quantized data through a series of index classes. Going from bottom to the top of the tree, neighboring coefficients are combined to form classes that represent some statistics of the quantization indices of these coefficients. Higher levels of the tree are constructed iteratively by repeating this class assignment to partition the coefficients into larger subsets. The class assignments are optimized using a rate-distortion cost analysis. The optimized tree is coded hierarchically from top to bottom by coding the class membership information at each level of the tree. Despite its simplicity, the algorithm produces PSNR results that are competitive with the state-of-art coders in literature.Yayın Hierarchical quantization indexing for wavelet and wavelet packet image coding(Elsevier Science BV, 2010-02) Ateş, Hasan Fehmi; Tamer, EnginIn this paper, we introduce the quantization index hierarchy, which is used for efficient coding of quantized wavelet and wavelet packet coefficients. A hierarchical classification map is defined in each wavelet subband, which describes the quantized data through a series of index classes. Going from bottom to the top of the tree, neighboring coefficients are combined to form classes that represent some statistics of the quantization indices of these coefficients. Higher levels of the tree are constructed iteratively by repeating this class assignment to partition the coefficients into larger Subsets. The class assignments are optimized using a rate-distortion cost analysis. The optimized tree is coded hierarchically from top to bottom by coding the class membership information at each level of the tree. Context-adaptive arithmetic coding is used to improve coding efficiency. The developed algorithm produces PSNR results that are better than the state-of-art wavelet-based and wavelet packet-based coders in literature.
