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Yayın A survey of algorithms and architectures for H.264 sub-pixel motion estimation(World Scientific, 2012-05) Fatemi, Mohammad Reza Hosseiny; Ateş, Hasan Fehmi; Salleh, Rosli BinThis paper reviews recent state-of-the-art H. 264 sub-pixel motion estimation (SME) algorithms and architectures. First, H.264 SME is analyzed and the impact of its functionalities on coding performance is investigated. Then, design space of SME algorithms is explored representing design problems, approaches, and recent advanced algorithms. Besides, design challenges and strategies of SME hardware architectures are discussed and promising architectures are surveyed. Further perspectives and future prospects are also presented to highlight emerging trends and outlook of SME designs.Yayın Disaster damage assessment of buildings using adaptive self-similarity descriptor(2016-08) Kahraman, Fatih; İmamoğlu, Mümin; Ateş, Hasan FehmiAssessment of damage caused by a disaster is significant for coordinating emergency response teams and planning emergency aid. In this letter, a robust method for rapid building damage assessment is proposed using pre- and postevent EO images and building footprints. The method uses a local self-similarity descriptor (SSD) for change detection in buildings, which is shown to be robust against variations in global illumination and small local deformations. The use of building footprints helps reduce the false alarms due to changes in nonbuilding areas. Footprint is also used to differentiate small and large buildings, extract the boundary region of a building, and adapt the descriptor computation accordingly. It is shown that the adaptive SSD provides a more accurate measure of local damage on the building. The 2010 Haiti Earthquake and Typhoon Haiyan 2013 Philippines are analyzed with the proposed method, and 75/82% true positive rate and 25/15% false positive rate are obtained for detection of collapsed buildings with respect to the ground truth data of UNITAR/UNOSAT and HOT.Yayın Spherical coding algorithm for wavelet image compression(IEEE-Inst Electrical Electronics Engineers Inc, 2009-05) Ateş, Hasan Fehmi; Orchard, Michael T.In recent literature, there exist many high-performance wavelet coders that use different spatially adaptive coding techniques in order to exploit the spatial energy compaction property of the wavelet transform. Two crucial issues in adaptive methods are the level of flexibility and the coding efficiency achieved while modeling different image regions and allocating bitrate within the wavelet subbands. In this paper, we introduce the "spherical coder," which provides a new adaptive framework for handling these issues in a simple and effective manner. The coder uses local energy as a direct measure to differentiate between parts of the wavelet subband and to decide how to allocate the available bitrate. As local energy becomes available at finer resolutions, i.e., in smaller size windows, the coder automatically updates its decisions about how to spend the bitrate. We use a hierarchical set of variables to specify and code the local energy up to the highest resolution, i.e., the energy of individual wavelet coefficients. The overall scheme is nonredundant, meaning that the subband information is conveyed using this equivalent set of variables without the need for any side parameters. Despite its simplicity, the algorithm produces PSNR results that are competitive with the state-of-art coders in literature.Yayın 3-D Mesh geometry compression with set partitioning in the spectral domain(IEEE-INST Electrical Electronics Engineers Inc, 2010-02) Bayazıt, Uluğ; Konur, Umut; Ateş, Hasan FehmiThis paper explains the development of a highly efficient progressive 3-D mesh geometry coder based on the region adaptive transform in the spectral mesh compression method. A hierarchical set partitioning technique, originally proposed for the efficient compression of wavelet transform coefficients in high-performance wavelet-based image coding methods, is proposed for the efficient compression of the coefficients of this transform. Experiments confirm that the proposed coder employing such a region adaptive transform has a high compression performance rarely achieved by other state of the art 3-D mesh geometry compression algorithms. A new, high-performance fixed spectral basis method is also proposed for reducing the computational complexity of the transform. Many-to-one mappings are employed to relate the coded irregular mesh region to a regular mesh whose basis is used. To prevent loss of compression performance due to the low-pass nature of such mappings, transitions are made from transform-based coding to spatial coding on a per region basis at high coding rates. Experimental results show the performance advantage of the newly proposed fixed spectral basis method over the original fixed spectral basis method in the literature that employs one-to-one mappings.Yayın Multi-hypothesis contextual modeling for semantic segmentation(Elsevier Science BV, 2019-01-01) Ateş, Hasan Fehmi; Sünetci, SercanSemantic segmentation (i.e. image parsing) aims to annotate each image pixel with its corresponding semantic class label. Spatially consistent labeling of the image requires an accurate description and modeling of the local contextual information. Segmentation result is typically improved by Markov Random Field (MRF) optimization on the initial labels. However this improvement is limited by the accuracy of initial result and how the contextual neighborhood is defined. In this paper, we develop generalized and flexible contextual models for segmentation neighborhoods in order to improve parsing accuracy. Instead of using a fixed segmentation and neighborhood definition, we explore various contextual models for fusion of complementary information available in alternative segmentations of the same image. In other words, we propose a novel MRF framework that describes and optimizes the contextual dependencies between multiple segmentations. Simulation results on two common datasets demonstrate significant improvement in parsing accuracy over the baseline approaches.Yayın Enhanced low bitrate H.264 video coding using decoder-side super-resolution and frame interpolation(SPIE-SOC Photo-Optical Instrumentation Engineers, 2013-07) Ateş, Hasan FehmiAdvanced inter-prediction modes are introduced recently in literature to improve video coding performances of both H.264 and High Efficiency Video Coding standards. Decoder-side motion analysis and motion vector derivation are proposed to reduce coding costs of motion information. Here, we introduce enhanced skip and direct modes for H.264 coding using decoder-side super-resolution (SR) and frame interpolation. P-and B-frames are downsampled and H.264 encoded at lower resolution (LR). Then reconstructed LR frames are super-resolved using decoder-side motion estimation. Alternatively for B-frames, bidirectional true motion estimation is performed to synthesize a B-frame from its reference frames. For P-frames, bicubic interpolation of the LR frame is used as an alternative to SR reconstruction. A rate-distortion optimal mode selection algorithm is developed to decide for each MB which of the two reconstructions to use as skip/direct mode prediction. Simulations indicate an average of 1.04 dB peak signal-to-noise ratio (PSNR) improvement or 23.0% bitrate reduction at low bitrates when compared with H.264 standard. The PSNR gains reach as high as 3.00 dB for inter-predicted frames and 3.78 dB when only B-frames are considered. Decoded videos exhibit significantly better visual quality as well.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.Yayın Rate-distortion and complexity optimized motion estimation for H.264 video coding(IEEE-INST Electrical Electronics Engineers Inc, 2008-02) Ateş, Hasan Fehmi; Altunbaşak, Yücel11.264 video coding standard supports several inter-prediction coding modes that use macroblock (MB) partitions with variable block sizes. Rate-distortion (R-D) optimal selection of both the motion vectors (MVs) and the coding mode of each MB is essential for an H.264 encoder to achieve superior coding efficiency. Unfortunately, searching for optimal MVs of each possible subblock incurs a heavy computational cost. In this paper, in order to reduce the computational burden of integer-pel motion estimation (ME) without sacrificing from the coding performance, we propose a R-D and complexity joint optimization framework. Within this framework, we develop a simple method that determines for each MB which partitions are likely to be optimal. MV search is carried out for only the selected partitions, thus reducing the complexity of the ME step. The mode selection criteria is based on a measure of spatiotemporal activity within the MB. The procedure minimizes the coding loss at a given level of computational complexity either for the full video sequence or for each single frame. For the latter case, the algorithm provides a tight upper bound on the worst case complexity/execution time of the ME module. Simulation results show that the algorithm speeds up integer-pel ME by a factor of up to 40 with less than 0.2 dB loss in coding efficiency.Yayın Analysis and design of low-cost bit-serial architectures for motion estimation in H.264/AVC(Springer, 2013-05) Fatemi, Mohammad Reza Hosseiny; Ateş, Hasan Fehmi; Salleh, Rosli BinVariable block-size motion estimation (VBSME) process occupies a major part of computation of an H.264 encoder, which is usually accelerated by bit-parallel hardware architectures with large I/O bit width to meet real-time constrains. However, such kind of architectures increase the area overhead and pin count, and therefore will not be suitable for area-constrained electronic consumer designs such as small portable multimedia devices. This paper addresses this problem by proposing two area efficient least significant bit (LSB) bit-serial architectures with small pin numbers. Both designs take advantage of data reusing technique in different ways for sum of absolute differences (SAD) computation and reading reference pixels, leading to a considerable reduction of memory bandwidth. The first architecture propagates the partial SAD and sum results and broadcasts the reference pixel rows whereas the second design reuse the SAD of small blocks and has a reconfigurable reference buffer leading to a better memory bandwidth when using hardware parallelism. The proposed designs benefit from several optimization techniques including an efficient serial absolute difference architecture, word length reduction by parallelism, bit truncation, mode filtering, and macroblock (MB) level subsampling, which significantly enhance their performances in terms of silicon area, throughput, latency, and power consumption. The first and second designs can support full search VBSME of 720 x 480 video with 30 frames per second (fps), two reference frames, and [-16, 15] search range at a clock frequency of 414 MHz with 29.28 k and 31.5 k gates, respectively.Yayın Fast algorithm analysis and bit-serial architecture design for sub-pixel motion estimation in H.264(World Scientific Publishing Company, 2010-12) Fatemi, Mohammad Reza Hosseiny; Ateş, Hasan Fehmi; Salleh, Rosli BinThe sub-pixel motion estimation (SME), together with the interpolation of reference frames, is a computationally extensive part of the H.264 encoder that increases the memory requirement 16-times for each reference frame. Due to the huge computational complexity and memory requirement of the H.264 SME, its hardware architecture design is an important issue especially in high resolution or low power applications. To solve the above difficulties, we propose several optimization techniques in both algorithm and architecture levels. In the algorithm level, we propose a parabolic based algorithm for SME with quarter-pixel accuracy which reduces the computational budget by 94.35% and the memory access requirement by 98.5% in comparison to the standard interpolate and search method. In addition, a fast version of the proposed algorithm is presented that reduces the computational budget 46.28% further while maintaining the video quality. In the architecture level, we propose a novel bit-serial architecture for our algorithm. Due to advantages of the bit-serial architecture, it has a low gate count, high speed operation frequency, low density interconnection, and a reduced number of I/O pins. Also, several optimization techniques including the sum of absolute differences truncation, source sharing exploiting and power saving techniques are applied to the proposed architecture which reduce power consumption and area. Our design can save between 57.71-90.01% of area cost and improves the macroblock (MB) processing speed between 1.7-8.44 times when compared to previous designs. Implementation results show that our design can support real time HD1080 format with 20.3 k gate counts at the operation frequency of 144.9 MHz.
