3-D Mesh geometry compression with set partitioning in the spectral domain

This 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.This work was supported in part by the Scientific and Technological Research Council of Turkey, and conducted under Project 106E064Publisher's Versio

Postprocessing of decoded color images by adaptive linear filtering

This paper presents an image adaptive linear filtering method for the reconstruction of the RGB (red, blue, green) color coordinates of a pixel from the lossy compressed luminance/chrominance color coordinates. In the absence of quantization noise, the RGB coordinates of a pixel can be perfectly reconstructed by employing a standard, fixed filter whose support includes only the luminance/chrominance coordinates at the spatial location of the pixel. However, in the presence of quantization noise, a filter with a larger support, that also spatially extends over the luminance/chrominance coordinate planes, is capable of exploiting the statistical dependence among the luminance/chrominance coordinate planes, and thereby yields more accurate reconstruction than the standard, fixed filter. We propose the optimal (in the minimum mean squared error sense) determination of the coefficients of this adaptive linear filter at the image encoder by solving a system of regression equations. When transmitted as side information to the image decoder, the filter coefficients need not incur significant overhead if they are quantized and compressed intelligently. Our simulation results demonstrate that the distortion of the decompressed color coordinate planes can be reduced by several tenths of a dB with negligible overhead rate by the application of our image adaptive linear filtering method.Publisher's Versio

Linear filtering of image subbands for low complexity postprocessing of decoded color images

In [1], image adaptive linear minimum mean squared error (LMMSE) filtering was proposed as an enhancement layer color image coding technique that exploited the statistical dependencies among the luminance/chrominance or Karhunen Loeve Transform (KLT) coordinate planes of a lossy compressed color image to enhance the red, blue, green (RGB) color coordinate planes of that image. In the current work, we propose the independent design and application of LMMSE filters on the subbands of a color image as a low complexity solution. Towards this end, only the coordinates of the neighbors of the filtered subband coefficient, that are sufficiently correlated with the corresponding coordinate of the filtered subband coefficient, are included in the support of the filter for each subband. Additionally, each subband LMMSE filter is selectively applied only on the high variance regions of the subband. Simulation results show that, at the expense of an insignificant increase in the overhead rate for the transmission of the coefficients of the filters and with about the same enhancement gain advantage, subband LMMSE filtering offers a substantial complexity advantage over fullband LMMSE filtering.Publisher's Versio

Classification-based macroblock layer rate control for low delay transmission of H.263 video

Puri and Aravind's method of macroblock bit count estimation for video rate control is based on the classification of the macroblock data into discrete classes and assigning a unique non-linear estimate for each class and quantization parameter pair. This method stands apart from other methods in the literature, since the model of the bit count versus the quantization parameter relation, parameterized by macroblock variance, is a discrete model generated solely from measurements, We extend their technique for low-delay video rate control (tight buffer regulation) in two ways. We propose a strategy of near-uniform quantization parameter assignments to the macroblocks of a frame that can come close to maximizing an objective spatial quality function, such as PSNR, over the entire frame. We also adaptively update the quantization parameter assignments for the yet to be coded macroblocks, after the encoding of each macroblock, to compensate for any errors in the bit count estimation of the encoded macroblock. Our experiments demonstrate that the proposed rate control method can more accurately control the number of bits expended for a frame, as well as yield a higher objective spatial quality than the method adopted by TMN8.Publisher's Versio

Algorithmic modifications to SPIHT

This paper proposes several low complexity algorithmic modifications to the SPIHT (Set Partitioning in Hierarchical Trees) image coding method of [3] The modifications exploit universal traits common to the real world images Approximately 1-2 % compression gain (bit rate reduction for a given mean squared error) has been obtained for the images in our test suite by incorporating all Of the Proposed modifications into SPIHT.Publisher's Versio

Üç boyutlu göz geometrisinin küme bölüntüleme ile verimli spektral kodlaması

3-B nesnelerin görselleştirilmesi uygulamalarında kullanılan tel filelerin ( gözlerin) geometrilerinin sıkıştırılması (DEERİNG, 1995)’deki ön görücü kodlamaya dayanan yöntem ile beraber rağbet gören bir araştırma alanı olmuştur. Yakın geçmişte araştırmacıların ilgi odağı ( KARNI, 2000) ve (KHODAKOVSKY, 2002)’dekine benzer dönüşüm tabanlı tel file geometri sıkıştırma yöntemlerine kaymıştır. (KARNI, 2000)’de klasik Fourier dönüşümünün 3 boyutlu tel ile geometrilerine genelleştirilmesi ile elde edilen dönüşümün düzenli olmayan tel file geometrilerine uygulanması ile özellikle düşük bit hızlarında yüksek sıkıştırma başarımı sağlanmıştır. Bu projedeki çalışmanın ilk aşamasında literatürdeki yüksek başarım sağlayan dalgacık dönüşüm tabanlı görüntü kodlama yöntemlerinde (ISLAM, 1999) (PEARLMAN, 2004) dalgacık dönüşüm katsayılarının verimli sıkıştırılması için kullanılmış olan sıradüzensel küme bölüntüleme tekniği, (KARNI, 2000)’de önerilen spektral dönüşüm katsayılarının bütün bit hızlarında verimli sıkıştırılması için uygulanmıştır. Kodlanan düzensiz tel filenin spektral taban vektörlerinden oluşturulan dönüşümün hesaplama karmaşıklığı çok yüksek olduğu için (KARNI, 2001)’de önerildiği gibi düzenli bir tel filenin değişmez spektral taban vektörleri ile sağlanan dönüşümün düzensiz tel filenin geometri kodlamasında kullanılması da incelenmiştir. Bu dönüşüm yönteminin uygulanmasında kodlanan düzensiz ve taban vektörleri kullanılan düzenli tel fileler arasındaki birebir eşlemlemenin eniyilikten uzak olduğu ve ve dolayısıyla sıkıştırma başarımı için yetersiz kaldığı gözlemlenmiştir. Düzenli ve düzensiz göz geometrileri arasında çoktan bire eşlemlemelerin kullanılmasını yüzsek bit hızlarında dönüşüm tabanlı kodlamadan uzamsal kodlamaya geçilmesi ile birleştiren önerilen alternatif yöntemin çok daha verimli olduğu gösterilmiştir.Mesh geometry compression, used in the applications related to the visualization of 3-D objects, has become a popular research area following the pioneering work of (DEERİND, 1995) that employs simple predictive coding. In the recent past, the mesh geometry compression methods of (KARNI, 2000) and (KHODAKOVSKY, 2002), regarded by most as the state of the art, are transform based. In (KARNI, 2000), the transform obtained by a generalization of the classical Fourier transform to the 3-D mesh geometries has been applied to irregular meshes to yield a high compression performance especially at low rates. In the first stage of the work of this project, a hierarchical set partitioning technique proposed for the efficient compression of wavelet transform coefficients in high performance wavelet based image coding methods (ISLAM, 1999) (PEARLMAN, 2004) in the literature has been applied to efficiently compress the coefficients of the spectral transform proposed in (KARNI, 2000). Since the computational complexity of the transform constructed by the spectral bases of the coded irregular mesh is overwhelming, the transform proposed in (KARNI, 2001) that is constructed by the fixed spectral basis of regular meshes has been investigated for use in geometry coding. In the implementation of this transformation method, the one- to- one mapping between the coded irregular mesh and the regular mesh whose basis are being used, has been observed to be rather suboptimal and yield insufficient compression performance. The proposed alternative method that combines the use of many-to-one maps between the regular and irregular mesh geometries and the transition from transform based coding to spatial coding at high rates has been shown to be more efficient.TÜBİTA

Cluster scheduling in range only tracking

This paper presents a sensor scheduling algorithm in a classical range-only target tracking application. Since only a small portion of deployed sensors can provide useful information about the position of target at a specific time instant, clustering method is utilized and Dynamic Cluster Scheduling (DCS) is applied instead of scheduling the individual sensor nodes. Particle filtering algorithm is employed for the tracking task, by processing data provided by the sensor nodes in the active cluster Active cluster is updated at each time step by comparing the position of master node in every cluster and the estimated target position. Cramer-Rao Bound is used as a comparison criteria for the proposed scheduling method. Simulation results show that activated sensor nodes during the overall tracking task in the region of interest are quite close to the scheduling results obtained with the Posterior Cramer-Rao Bound which sets a theoretical lower limit on the estimator performance

Multipath querying of hierarchically tree structured document databases in vector spaces

Web sayfaları, makaleler, kitap veya dergi isimlerinden oluşan büyük doküman yığınları üzerinde sorgulama yaparken dokümanları vektörlere ve doküman topluluklarını matrislere indirgemek sorgulamaları çok daha hızlandırır ve kolaylaştırır. Kullanılan matris ve vektörlerin boyutlarının büyüklüğü sebebiyle sorgulamalarda ortaya çıkan yüksek hesap karmaşıklığından kaçınılması için literatürde tekil değer ayrışımı ve ana bileşen analizi gibi boyut indirgeme yöntemleri önerilmiştir. Boyut indirgemeyle beraber hesap karmaşıklığını indirgeme için [12]’ de veritabanını sıradüzensel ağaç yapısı ile düzenleme ve bu yapı üzerinden tekli ve çoklu yollar kullanarak sorgulama önerilmiştir. Bu bildiride statik ve uyarlanabilir çoklu yolla sorgulama yöntemlerinin hesap karmaşıklığı başarım ödünleşimleri incelenmekte ve karşılaştırılmaktadır.Representation of large document databases consisting of web pages, articles, book and magazine titles in terms of matrices for the purpose of text querying and retrieval simplifies and expedites the querying process. In the literature, dimensionality reduction techniques based on singular value decomposition and principal component analysis have been proposed to reduce the high computational complexity resulting from the use of high dimensional matrices and vectors. In [12], organization of the text database in the form of a hierarchical tree structure, and single path and multi path querying over this structure, was proposed as a technique to reduce the computational complexity in addition to dimensionality reduction. In this paper, we analyze and compare the tradeoff between the computational complexity and the performance of the static and adaptive multipath querying methods by varying the number of paths.Publisher's Versio

Cluster scheduling in range-only tracking with particle filtering

Bu çalışmada, uzaklık ölçer algılayıcılarla hedef takibi uygulamasında algılayıcı çizelgeleme problemi ele alınmıştır. Çok algılayıcılı uygulamalarda algılayıcıların yönetimi ürettikleri verilerin sınıflandırılması için olduğu kadar algılayıcıların verimli kullanımı için de gereklidir. Algılayıcı yönetimindeki önemli hususlardan biri algılayıcı çizelgelemesidir. Algılayıcıları çizelgeleyerek bant genişliği, güç, ve hesaplamada ciddi ölçüde kazanımlar sağlanabilir.Sensor scheduling problem in a range-only target tracking application is addressed in this paper. In multi-sensor applications management of sensors is necessary for the classification of data they produce and for the efficient use of sensors as well. One of the important aspects in sensor management is the sensor scheduling. By scheduling the sensors, serious reductions can be achieved in the cost of bandwidth, power, and computation. Due to non-linearity of the problem itself, proposed solution is presented in the framework of non-linear Bayesian estimation.Publisher's Versio

Cluster based sensor scheduling in a target tracking application with particle filtering

In multi-sensor applications management of sensors is necessary for the classification of data they produce and for the efficient use of sensors as well. One of the important aspects in sensor management is the sensor scheduling. By scheduling the sensors, serious reductions can be achieved in the cost of bandwidth, power, and computation. In this work a simple solution for the problem of sensor scheduling in a multi-sensor target tracking application is presented. Due to non-linearity of the problem itself, proposed solution is presented in the framework of non-linear Bayesian estimation.This research has been funded by the The Scientific & Technological Research Council of Turkey (TUB ITAK), Project No: 104E130 and also supported in part by the Research Fund of the University of Istanbul. Project number: 513/05052006.Publisher's Versio