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Browsing by Subject "Image coding"

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    A 2-D orientation-adaptive prediction filter in lifting structures for image coding
    (Institute of Electrical and Electronics Engineers, 2006) Gerek, Ö. N.; Çetin, A. Enis
    Lifting-style implementations of wavelets are widely used in image coders. A two-dimensional (2-D) edge adaptive lifting structure, which is similar to Daubechies 5/3 wavelet, is presented. The 2-D prediction filter predicts the value of the next polyphase component according to an edge orientation estimator of the image. Consequently, the prediction domain is allowed to rotate ±45° in regions with diagonal gradient. The gradient estimator is computationally inexpensive with additional costs of only six subtractions per lifting instruction, and no multiplications are required.
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    Adaptive polyphase subband decomposition structures for image compression
    (IEEE, 2000) Gerek, Ö. N.; Çetin, A. Enis
    Subband decomposition techniques have been extensively used for data coding and analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to different spectral regions of the original data. However, this approach leads to various artifacts in images having spatially varying characteristics, such as images containing text, subtitles, or sharp edges. In this paper, adaptive filter banks with perfect reconstruction property are presented for such images. The filters of the decomposition structure which can be either linear or nonlinear vary according to the nature of the signal. This leads to improved image compression ratios. Simulation examples are presented.
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    Binary morphological subband decomposition for image coding
    (IEEE, 1996) Gürcan, Metin Nafi; Gerek, Ömer Nezih; Çetin, A. Enis
    In this paper a binary waveform coding method based on morphological subband decomposition coupled with embedded zero-tree and entropy coding is described. This method can be utilized in text compression or bit-plane coding of images. Binary morphological subband decomposition operations are carried out in the Gallois Field, resulting in a computationally efficient structure. Simulation studies are presented.
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    Block wavelet transforms for image coding
    (IEEE, 1993) Çetin, A. Enis; Gerek, Ö. N.; Ulukuş, Ş.
    In this paper, a new class of block transforms is presented. These transforms are constructed from subband decomposition filter banks corresponding to regular wavelets. New transforms are compared to the discrete cosine transform (DCT). Image coding schemes that employ the block wavelet transform (BWT) are developed. BWT's can be implemented by fast (O(N log N)) algorithms.
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    Coding of fingerprint images using binary subband decomposition and vector quantization
    (SPIE, 1998-01) Gerek, Ömer N.; Çetin, A. Enis
    In this paper, compression of binary digital fingerprint images is considered. High compression ratios for fingerprint images is essential for handling huge amount of images in databases. In our method, the fingerprint image is first processed by a binary nonlinear subband decomposition filter bank and the resulting subimages are coded using vector quantizers designed for quantizing binary images. It is observed that the discriminating properties of the fingerprint, images are preserved at very low bit rates. Simulation results are presented.
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    Compression of images in CFA format
    (IEEE, 2006) Cüce, Halil İbrahim; Çetin, A. Enis; Davey, M. K.
    In this paper, images in Color Filter Array (CFA) format are compressed without converting them to full-RGB color images. Green pixels are extracted from the CFA image data and placed in a rectangular array, and compressed using a transform based method without estimating the corresponding luminance values. In addition, two sets of color difference (or chrominance) coefficients are obtained corresponding to the red and blue pixels of the CFA data and they are also compressed using a transform based method. The proposed method produces better PSNR values compared to the standard approach of bilinear interpolation followed by compression.
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    DCT coding of nonrectangularly sampled images
    (IEEE, 1994) Gündüzhan, E.; Çetin, A. Enis; Tekalp, A. M.
    Discrete cosine transform (DCT) coding is widely used for compression of rectangularly sampled images. In this letter, we address efficient DCT coding of nonrectangularly sampled images. To this effect, we discuss an efficient method for the computation of the DCT on nonrectangular sampling grids using the Smith-normal decomposition. Simulation results are provided.
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    Error resilient layered stereoscopic video streaming
    (IEEE, 2007) Tan, Ahmet Serdar; Aksay, A.; Bilen, Ç.; Bozdağı-Akar, G.; Arıkan, Erdal
    In this paper, error resilient stereoscopic video streaming problem is addressed. Two different Forward Error Correction (FEC) codes namely Systematic LT and RS codes are utilized to protect the stereoscopic video data against transmission errors. Initially, the stereoscopic video is categorized in 3 layers with different priorities. Then, a packetization scheme is used to increase the efficiency of error protection. A comparative analysis of RS and LT codes are provided via simulations to observe the optimum packetization and UEP strategies.
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    Estimation of depth fields suitable for video compression based on 3-D structure and motion of objects
    (Institute of Electrical and Electronics Engineers, 1998-06) Alatan, A. A.; Onural, L.
    Intensity prediction along motion trajectories removes temporal redundancy considerably in video compression algorithms. In three-dimensional (3-D) object-based video coding, both 3-D motion and depth values are required for temporal prediction. The required 3-D motion parameters for each object are found by the correspondence-based E-matrix method. The estimation of the correspondences - two-dimensional (2-D) motion field - between the frames and segmentation of the scene into objects are achieved simultaneously by minimizing a Gibbs energy. The depth field is estimated by jointly minimizing a defined distortion and bitrate criterion using the 3-D motion parameters. The resulting depth field is efficient in the rate-distortion sense. Bit-rate values corresponding to the lossless encoding of the resultant depth fields are obtained using predictive coding; prediction errors are encoded by a Lempel-Ziv algorithm. The results are satisfactory for real-life video scenes.
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    Haber videolarında nesne tanıma ve otomatik etiketleme
    (IEEE, 2006-04) Baştan, Muhammet; Duygulu, Pınar
    We propose a new approach to object recognition problem motivated by the availability of large annotated image and video collections. Similar to translation from one language to another, this approach considers the object recognition problem as the translation of visual elements to words. The visual elements represented in feature space are first categorized into a finite set of blobs. Then, the correspondences between the blobs and the words are learned using a method adapted from Statistical Machine Translation. Finally, the correspondences, in the form of a probability table, are used to predict words for particular image regions (region naming), for entire images (auto-annotation), or to associate the automatically generated speech transcript text with the correct video frames (video alignment). Experimental results are presented on TRECVID 2004 data set, which consists of about 150 hours of news videos associated with manual annotations and speech transcript text. © 2006 IEEE.
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    Impact of scalability in video transmission in promotion-capable differentiated services networks
    (IEEE, 2002-09) Gürses, E.; Akar, G. B.; Akar, Nail
    Transmission of high quality video over the Internet faces many challenges including unpredictable packet loss characteristics of the current Internet and the heterogeneity of receivers in terms of their bandwidth and processing capabilities. To address these challanges, we propose an architecture in this paper that is based on the temporally scalable and error resilient video coding mode of the H.263+ codec. In this architecture, the video frames will be transported over a new generation IP network that supports differentiated services (Diffserv). We also propose a novel Two Rate Three Color Promotion-Capable Marker (trTCPCM) to be used at the edge of the diffserv network. Our simulation study demonstrates that an average of 30 dB can be achieved in case of highly congested links.
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    An improvement to MBASIC algorithm for 3-D motion and depth estimation
    (IEEE, 1994) Bozdağı, G.; Tekalp, A. M.; Onural, L.
    In model-based coding of facial images, the accuracy of motion and depth parameter estimates strongly affects the coding efficiency. MBASIC is a simple and effective iterative algorithm (recently proposed by Aizawa et al.) for 3-D motion and depth estimation when the initial depth estimates are relatively accurate. In this correspondence, we analyze its performance in the presence of errors in the initial depth estimates and propose a modification to MBASIC algorithm that significantly improves its robustness to random errors with only a small increase in the computational load.
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    Iterative technique for 3-D motion estimation in videophone applications
    (IEEE, 1994-04) Bozdağı, Gözde; Tekalp, A. M.; Onural, Levent
    In object based coding of facial images, the accuracy of motion and depth parameter estimates strongly affects the coding efficiency. We propose an improved algorithm based on stochastic relaxation for 3-D motion and depth estimation that converges to true motion and depth parameters even in the presence of 50% error in the initial depth estimates. The proposed method is compared with an existing algorithm (MBASIC) in case of different number of point correspondences. The simulation results show that the proposed method provides significantly better results than the MBASIC algorithm.
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    Joint estimation and optimum encoding of depth field for 3-D object-based video coding
    (IEEE, 1996-09) Alatan, A. Aydın; Onural, Levent
    3-D motion models can be used to remove temporal redundancy between image frames. For efficient encoding using 3-D motion information, apart from the 3-D motion parameters, a dense depth field must also be encoded to achieve 2-D motion compensation on the image plane. Inspiring from Rate-Distortion Theory, a novel method is proposed to optimally encode the dense depth fields of the moving objects in the scene. Using two intensity frames and 3-D motion parameters as inputs, an encoded depth field can be obtained by jointly minimizing a distortion criteria and a bit-rate measure. Since the method gives directly an encoded field as an output, it does not require an estimate of the field to be encoded. By efficiently encoding the depth field during the experiments, it is shown that the 3-D motion models can be used in object-based video compression algorithms.
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    Linear and nonlinear temporal prediction employing lifting structures for scalable video coding
    (IEEE, 2006-09) Töreyin, B. Uğur; Trocan, M.; Pesquet-Popescu, B.; Çetin, A. Enis
    Scalable 3D video codecs based on wavelet lifting structures have attracted recently a lot of attention, due to their compression performance comparable with that of state-of-art hybrid codecs. In this work, we propose a set of linear and nonlinear predictors for the temporal prediction step in lifting implementation. The predictor uses pixels on the motion trajectories of the frames in a window around the pixel to be predicted to improve the quality of prediction. Experimental results show that the video quality as well as PSNR values are improved with the proposed prediction method.
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    Linear/nonlinear adaptive polyphase subband decomposition structures for image compression
    (IEEE, 1998-05) Gerek, Ömer N.; Çetin, A. Enis
    Subband decomposition techniques have been extensively used for data coding and analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to different spectral bands of the original data. However, this approach leads to various artifacts in images containing text, subtitles, or sharp edges. In this paper, adaptive filter banks with perfect reconstruction property are presented for such images. The filters of the decomposition structure vary according to the nature of the signal. This leads to higher compression ratios for images containing subtitles compared to fixed filter banks. Simulation examples are presented.
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    LMS based adaptive prediction for scalable video coding
    (IEEE, 2006-05) Töreyin, B. Uğur; Trocan, M.; Pesquet-Popescu, B.; Çetin, A. Enis
    3D video codecs have attracted recently a lot of attention, due to their compression performance comparable with that of state-of-art hybrid codecs and due to their scalability features. In this work, we propose a least mean square (LMS) based adaptive prediction for the temporal prediction step in lifting implementation. This approach improves the overall quality of the coded video, by reducing both the blocking and ghosting artefacts. Experimental results show that the video quality as well as PSNR values are greatly improved with the proposed adaptive method, especially for video sequences with large contrast between the moving objects and the background and for sequences with illumination variations. © 2006 IEEE.
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    Lossless image compression by LMS adaptive filter banks
    (Elsevier, 2001) Öktem, R.; Çetin, A. Enis; Gerek, O. N.; Öktem, L.; Egiazarian, K.
    A lossless image compression algorithm based on adaptive subband decomposition is proposed. The subband decomposition is achieved by a two-channel LMS adaptive filter bank. The resulting coefficients are lossy coded first, and then the residual error between the lossy and error-free coefficients is compressed. The locations and the magnitudes of the nonzero coefficients are encoded separately by an hierarchical enumerative coding method. The locations of the nonzero coefficients in children bands are predicted from those in the parent band. The proposed compression algorithm, on the average, provides higher compression ratios than the state-of-the-art methods.
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    Lossless image compression using an edge adapted lifting predictor
    (IEEE, 2005-09) Gerek, Ö. N.; Çetin, A .Enis
    We present a novel and computationally simple prediction stage in a Daubechies 5/3 - like lifting structure for lossless image compression. In the 5/3 wavelet, the prediction filter predicts the value of an odd-indexed polyphase component as the mean of its immediate neighbors belonging to the even-indexed polyphase components. The new edge adaptive predictor, however, predicts according to a local gradient direction estimator of the image. As a result, the prediction domain is allowed to flip + or - 45 degrees with respect to the horizontal or vertical axes in regions with diagonal gradient. We have obtained good compression results with conventional lossless wavelet coders. © 2005 IEEE.
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    Morphological subband decomposition structure using GF(N) arithmetic
    (IEEE, 1996-09) Gürcan, Metin Nafi; Çetin, A. Enis; Gerek, Ömer, N.
    Linear filter banks with critical subsampling and perfect reconstruction (PR) property have received much interest and found numerous applications in signal and image processing. Recently, nonlinear filter bank structures with PR and critical subsampling have been proposed and used in image coding. In this paper, it is shown that PR nonlinear subband decomposition can be performed using the Gallois Field (GF) arithmetic. The result of the decomposition of an n-ary (e.g. 256-ary) input signal is still n-ary at different resolutions. This decomposition structure can be utilized for binary and 2k (k is an integer) level signal decompositions. Simulation studies are presented.
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