Browsing by Subject "Image compression"

Now showing 1 - 20 of 27

Open Access
3D model compression using connectivity-guided adaptive wavelet transform built into 2D SPIHT
(Academic Press, 2010-01) Köse K.; Çetin, A. Enis; Güdükbay, Uğur; Onural, L.
Connectivity-Guided Adaptive Wavelet Transform based mesh compression framework is proposed. The transformation uses the connectivity information of the 3D model to exploit the inter-pixel correlations. Orthographic projection is used for converting the 3D mesh into a 2D image-like representation. The proposed conversion method does not change the connectivity among the vertices of the 3D model. There is a correlation between the pixels of the composed image due to the connectivity of the 3D mesh. The proposed wavelet transform uses an adaptive predictor that exploits the connectivity information of the 3D model. Known image compression tools cannot take advantage of the correlations between the samples. The wavelet transformed data is then encoded using a zero-tree wavelet based method. Since the encoder creates a hierarchical bitstream, the proposed technique is a progressive mesh compression technique. Experimental results show that the proposed method has a better rate distortion performance than MPEG-3DGC/MPEG-4 mesh coder.
Open Access
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.
Open Access
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.
Open Access
Content-adaptive color transform for image compression
(IEEE, 2011) Suhre, Alexander; Köse, Kıvanç; Çetin, A. Enis; Gürcan, Metin N.
In this paper, an adaptive color transform for image compression is introduced. In each block of the image coefficients of the color transform are determined from the previously compressed neighboring blocks using weighted sums of the RGB pixel values, making the transform block-specific. There is no need to transmit or store the transform coefficients because they are estimated from previous blocks. The compression efficiency of the transform is demonstrated using the JPEG image coding scheme. In general, the suggested transformation results in better PSNR values for a given compression level.
Open Access
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.
Open Access
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.
Open Access
An image watermarking algorithm via Zero Assigned Filter Banks
(IEEE, 2005-12) Yücel, Zeyep; Özgüler, A. Bülent
In this paper a new method for digital image watermarking based on Zero Assigned Filter Banks and Embedded Zero Tree Wavelet (EZW) algorithm is presented. An image is partitioned into 128 × 128 subblocks and each block is processed in a three stage decomposition structure by a filter bank which is assigned a zero around the stop band. The coefficients to be marked are chosen according to the EZW algorithm. This method not only provides a robust watermarking scheme but may also be used as an effective compression strategy. The algorithm is tested under white Gaussian noise and against JPEG compression and it is observed to be robust even when exposed to high levels of corruption. © 2005 IEEE.
Open Access
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.
Open Access
Key frame selection from MPEG video data
(SPIE, 1997-02) Gerek, Ömer. N.; Altunbaşak, Y.
This paper describes a method for selecting key frames by using a number of parameters extracted from the MPEG video stream. The parameters are directly extracted from the compressed video stream without decompression. A combination of these parameters are then used in a rule based decision system. The computational complexity for extracting the parameters and for key frame decision rule is very small. As a results, the overall operation is very quickly performed and this makes our algorithm handy for practical purposes. The experimental results show that this method can select the distinctive frames of video streams successfully.
Open Access
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.
Open Access
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.
Open Access
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.
Open Access
Motion-compensated prediction based algorithm for medical image sequence compression
(Elsevier BV, 1995-09) Oǧuz, S. H.; Gerek, Ö. N.; Çetin, A. Enis
A method for irreversible compression of medical image sequences is described. The method relies on discrete cosine transform and motion-compensated prediction to reduce intra- and inter-frame redundancies in medical image sequences. Simulation examples are presented.
Open Access
Moving region detection in compressed video
(Springer, 2004) Töreyin, B. U.; Çetin, A. Enis; Aksay, A.; Akhan, M. B.
In this paper, an algorithm for moving region detection in compressed video is developed. It is assumed that the video can be compressed either using the Discrete Cosine Transform (DOT) or the Wavelet Transform (WT). The method estimates the WT of the background scene from the WTs of the past image frames of the video. The WT of the current image is compared with the WT of the background and the moving objects are determined from the difference. The algorithm does not perform inverse WT to obtain the actual pixels of the current image nor the estimated background. In the case of DOT compressed video, the DC values of 8 by 8 image blocks of Y, U and V channels are used for estimating the background scene. This leads to a computationally efficient method and a system compared to the existing motion detection methods. © Springer-Verlag 2004.
Open Access
Moving region detection in wavelet compressed video
(IEEE, 2004) Töreyin, B. Uğur; Çetin, A. Enis; Aksay, Anıl; Akhan, M. B.
In many vision based surveillance systems the video is stored in wavelet compressed form. In this study, an algorithm for moving object and region detection in video that is compressed using a wavelet transform (WT) is developed. The algorithm estimates the WT of the background scene from the WTs of the past image frames of the video. The WT of the current image is compared with the WT of the background and the moving objects are determined from the difference. The algorithm does not perform inverse WT to obtain the actual pixels of the current image nor the estimated background. This leads to a computationally efficient method and a system compared to the existing motion estimation methods.
Open Access
Multiresolution block coding method for visualization of compressed images in multimedia applications
(Society of Photo-Optical Instrumentation Engineers, 1994) Gerek, O. N.; Cetin, E. A.
Multimedia and Picture Archiving and Communication System (PACS) applications require efficient ways of handling images for communication and visualization. In many Visual Information and Management Systems (VIMS), it may be required to get quick responses to queries. Usually, a VIMS database has a huge number of images and may provide lots of images for each query. For example, in a PACS, the VIMS provides 10 to 100 images for a typical query. Only a few of these images may actually be needed. In order to find the useful ones, the user has to preview each image by fully decompressing it. This is neither computationally efficient, nor user friendly. In this paper, we propose a scheme which provides a magnifying glass type previewing feature. With this method, a multiresolution previewing without decompressing the whole image is possible. Our scheme is based on block transform coding which is the most widely used technique in image and video coding. In the first step of our scheme, all of the queried images are displayed in the lowest possible resolution (constructed from the DC coefficients of the coded blocks). If the user requests more information for a region of a particular image by specifying its size and place, then that region is hierarchically decompressed and displayed. In this way, large amounts of computations and bandwidth usage are avoided and a good user interface is accomplished. This method changes the ordering strategy of transform coefficients, thus reduces the compression ratio, however this effect is small.
Open Access
Near-lossless image compression techniques
(S P I E - International Society for Optical Engineering, 1998) Ansari, R.; Memon, N.; Ceran, E.
Predictive and multiresolution techniques for near- lossless image compression based on the criterion of maximum allowable deviation of pixel values are investigated. A procedure for near-lossless compression using a modification of lossless predictive coding techniques to satisfy the specified tolerance is described. Simulation results with modified versions of two of the best lossless predictive coding techniques known, CALIC and JPEG-LS, are provided. Application of lossless coding based on reversible transforms in conjunction with prequantization is shown to be inferior to predictive techniques for near-lossless compression. A partial embedding two-layer scheme is proposed in which an embedded multiresolution coder generates a lossy base layer, and a simple but effective context-based lossless coder codes the difference between the original image and the lossy reconstruction. Results show that this lossy plus near-lossless technique yields compression ratios close to those obtained with predictive techniques, while providing the feature of a partially embedded bit-stream. © 1998 SPIE and IS&T.
Open Access
Nonrectangular wavelets for multiresolution mesh analysis and compression
(SPIE, 2006) Köse, Kıvanç; Çetin, A. Enis; Güdükbay, Uğur; Onural, Levent
We propose a new Set Partitioning In Hierarchical Trees (SPIHT) based mesh compression framework. The 3D mesh is first transformed to 2D images on a regular grid structure. Then, this image-like representation is wavelet transformed and SPIHT is applied on the wavelet domain data. The method is progressive because the resolution of the reconstructed mesh can be changed by varying the length of the ID data stream created by SPIHT algorithm. Nearly perfect reconstruction is possible if full length of 1D data is received.
Open Access
Novel methods for microscopic image processing, analysis, classification and compression
(2013) Suhre, Alexander
Microscopic images are frequently used in medicine and molecular biology. Many interesting image processing problems arise after the initial data acquisition step, since image modalities are manifold. In this thesis, we developed several algorithms in order to handle the critical pipeline of microscopic image storage/ compression and analysis/classification more efficiently. The first step in our processing pipeline is image compression. Microscopic images are large in size (e.g. 100K-by-100K pixels), therefore finding efficient ways of compressing such data is necessary for efficient transmission, storage and evaluation. We propose an image compression scheme that uses the color content of a given image, by applying a block-adaptive color transform. Microscopic images of tissues have a very specific color palette due to the staining process they undergo before data acquisition. The proposed color transform takes advantage of this fact and can be incorporated into widely-used compression algorithms such as JPEG and JPEG 2000 without creating any overhead at the receiver due to its DPCM-like structure. We obtained peak signal-to-noise ratio gains up to 0.5 dB when comparing our method with standard JPEG. The next step in our processing pipeline is image analysis. Microscopic image processing techniques can assist in making grading and diagnosis of images reproducible and by providing useful quantitative measures for computer-aided diagnosis. To this end, we developed several novel techniques for efficient feature extraction and classification of microscopic images. We use region co-difference matrices as inputs for the classifier, which have the main advantage of yielding multiplication-free computationally efficient algorithms. The merit of the co-difference framework for performing some important tasks in signal processing is discussed. We also introduce several methods that estimate underlying probability density functions from data. We use sparsity criteria in the Fourier domain to arrive at efficient estimates. The proposed methods can be used for classification in Bayesian frameworks. We evaluated the performance of our algorithms for two image classification problems: Discriminating between different grades of follicular lymphoma, a medical condition of the lymph system, as well as differentiating several cancer cell lines from each another. Classification accuracies over two large data sets (270 images for follicular lymphoma and 280 images for cancer cell lines) were above 98%.
Open Access
Object based 3-D motion and structure estimation
(IEEE, 1996) Alatan, A. Aydın; Onural, Levent
Motion analysis is the most crucial part of object-based coding. A motion in 3-D environment can be analyzed better by using a 3-D motion model compared to its 2-D counterpart and hence may improve coding efficiency. Gibbs formulated joint segmentation and estimation of 2-D motion not only improves performance, but also generates robust point correspondences which are necessary for linear 3-D motion estimation algorithms. Estimated 3-D motion parameters are used to find the structure of the previously segmented objects by minimizing another Gibbs energy. Such an approach achieves error immunity compared to linear algorithms. Experimental results are promising and hence the proposed motion and structure analysis method is a candidate to be used in object-based (or even knowledge-based) video coding schemes.