From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

MUCKE aims to mine a large volume of images, to structure them conceptually and to use this conceptual structuring in order to improve large-scale image retrieval. The last decade witnessed important progress concerning low-level image representations. However, there are a number problems which need to be solved in order to unleash the full potential of image mining in applications. The central problem with low-level representations is the mismatch between them and the human interpretation of image content. This problem can be instantiated, for instance, by the incapability of existing descriptors to capture spatial relationships between the concepts represented or by their incapability to convey an explanation of why two images are similar in a content-based image retrieval framework. We start by assessing existing local descriptors for image classification and by proposing to use co-occurrence matrices to better capture spatial relationships in images. The main focus in MUCKE is on cleaning large scale Web image corpora and on proposing image representations which are closer to the human interpretation of images. Consequently, we introduce methods which tackle these two problems and compare results to state of the art methods. Note: some aspects of this deliverable are withheld at this time as they are pending review. Please contact the authors for a preview.

http://ieeexplore.ieee.org/iel2/4524/12820/00592460.pdf

Image Processing

IEEE Transactions on Pattern Analysis and Machine Intelligence

Real and Complex Analysis

Image change detectio algorithms : A systematic survey

Given two CT thorax images from the same patient taken at two different points in time, a detailed follow-up
assessment of pleural thickenings and their growth requires a registration of the regarded image regions. While
the spatio-temporal matching of thickenings could be achieved by a rigid registration, the direct visual comparison
or the combination of thickening segmentations from different points in time require a more precise registration.
We present a new method which provides a non-rigid registration of the 3D image data in the region close to the
lung surface, where pleural thickenings are located. A B-spline based approach is used to compensate the non-rigid
deformations of the lungs. The control-grid for the B-splines is determined using a non-iterative method,
which requires matched feature points from the registered image pair. However, current non-rigid registration
methods compensate all changes of the lung surface. This is in our case explicitly undesired for changes caused
by pleural thickenings. Therefore, our approach takes the thickenings into account by choosing feature points
not directly located on the lung surface. The number of feature points is reduced and only strong features are
kept for a 3D block matching.

/pdf/non-rigid-surface-proximity-registration-of-ct-images-rdvycrpugl.pdf

Non-rigid surface proximity registration of CT images considering the influence of pleural thickenings

Kurzfassung. Bei dem nuklearmedzinischen funktionalen Bildgebungsverfahren SPECT werden zur Diagnostik der koronaren Herzkrankheit (KHK) üblicherweise zwei getrennte Aufnahmen in Ruhe und unter Belastung verglichen. In diesem Beitrag wird anhand von Phantommessungen und ersten Patientendaten ein Protokoll untersucht, bei dem mit nur einer SPECT-Aufnahme der Ruheund Belastungszustand gleichzeitig extrahiert werden können. Dies wird durch Applikation der beiden Tracer Tc-99m in Ruhe und Tl-201 unter Belastung sowie durch ein Rekonstruktionsverfahren mit einer auf Monte-Carlo Simulationen beruhenden Streukorrektur ermöglicht. Dadurch kann sowohl die für eine Studie benötigte Zeit reduziert, wie auch die Registrierung der Bilder der beiden Aufnahmen umgangen werden. Die hier vorgestellten Phantomund Patientendaten zeigen eine gute für die klinische Beurteilung ausreichende Bildqualität und geben Anlass für weitere klinische Studien.

Thallium-Stress, Technetium-Rest Protokoll für Cardiac SPECT.

Keratin polypeptides are major components of the epithelial cytoskeleton forming a filamentous 3D-network. Like intermediate filament polypeptides of other cell types, keratins make up a stable, but elastic network that is responsible for mechanical stress resilience. At the same time the keratin network is able to change its shape during development, cell division, metastasis and cell migration.

In vivo imaging and quantification of the continuous keratin filament network turnover

We present a novel and efficient approach for 3D motion estimation of keratin intermediate filaments in vitro. Keratin filaments are elastic cables forming a complex scaffolding within epithelial cells. To understand the mechanisms of filament formation and network organisation under physiological and pathological conditions, quantitative measurements of dynamic network alterations are essential. Therefore we acquired time-lapse series of 3D images using a confocal laser scanning microscope. Based on these image series, we show that a dense vector field can be computed such that the displacements from one frame to the next can be determined. Our method is based on a two-step registration process: First, a rigid pre-registration is applied in order to compensate for possible global cell movement. This step enables the subsequent nonrigid registration to capture only the sought local deformations of the filaments. As the transformation model of the deformable registration algorithm is based on Free Form Deformations, it is well suited for modeling filament network dynamics. The optimization is performed using efficient linear programming techniques such that the huge amount of image data of a time series can be efficiently processed. The evaluation of our results illustrates the potential of our approach.

3D motion analysis of keratin filaments in living cells

In continuous X-ray fluoroscopy images are sometimes blurred uniformly due to motion of the operating table. Additionally, low-dose fluoroscopy images are degraded by relatively strong quantum noise, which is not affected by the blur. We quantify the degradation due to motion blur by assessing the blur's effect on the Detective Quantum Efficiency (DQE), which captures the signal- and noise transfer properties of an imaging system. The estimation of the motion blur parameters, viz. direction and extent, is carried out one after the other. The central idea for direction detection is to apply an inertia-like matrix to the global spectrum of the degraded image, which assesses the anisotropy caused by the blur. Once the blur direction is obtained by this tensor approach, its extent is identified from an estimated power spectrum or bispectrum slice along this direction. The decision for either method is based on the eigenvalues of the inertia matrix. The blur parameters are used as input for a nonlinear Maximum-a- posteriori restoration technique based on a Generalized Gauss- Markov Random field for which several efficient optimization strategies are presented. This approach includes a thresholdless edge model. The DQE is generalized as a quality measure to assess the signal- and noise transfer properties of the restoration method.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Til Aach

Papers

Non-rigid surface proximity registration of CT images considering the influence of pleural thickenings

Thallium-Stress, Technetium-Rest Protokoll für Cardiac SPECT.

In vivo imaging and quantification of the continuous keratin filament network turnover

3D motion analysis of keratin filaments in living cells

Motion blur in fluoroscopy: effects, identification, and restoration