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Spatially adaptive alpha-rooting in BM3D sharpening

Spatially adaptive alpha-rooting in BM3D sharpening

引用

Conference on image processing: algorithms and systems ix

作者： Makitalo, Markku Foi, Alessandro Tampere Univ Technol Dept Signal Proc FIN-33101 Tampere Finland

ISBN: (纸本)9780819484079

The block-matching and 3-D filtering (BM3D) algorithm is currently one of the most powerful and effective image denoising procedures. It exploits a specific nonlocal image modelling through grouping and collaborative filtering. Grouping finds mutually similar 2-D image blocks and stacks them together in 3-D arrays. Collaborative filtering produces individual estimates of all grouped blocks by filtering them jointly, through transform-domain shrinkage of the 3-D arrays (groups). BM3D can be combined with transform-domain alpha-rooting in order to simultaneously sharpen and denoise the image. Specifically, the thresholded 3-D transform-domain coefficients are modified by taking the alpha-root of their magnitude for some alpha > 1, thus amplifying the differences both within and between the grouped blocks. While one can use a constant (global) alpha throughout the entire image, further performance can be achieved by allowing different degrees of sharpening in different parts of the image, based on content-dependent information. We propose to vary the value of alpha used for sharpening a group through weighted estimates of the low-frequency, edge, and high-frequency content of the average block in the group. This is shown to be a viable approach for image sharpening, and in particular it can provide an improvement (both visually and in terms of PSNR) over its global non-adaptive counterpart.

关键词： 3D image processing Point spread functions Visualization Affine motion model image filtering Filtering (signal processing) image processing image denoising image visualization Modeling

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image Interpolation Based on a Multi-resolution Directional Map

Image Interpolation Based on a Multi-resolution Directional ...

引用

Conference on image processing: algorithms and systems ix

作者： Van Reeth, Eric Bertolino, Pascal Nicolas, Marina STMicroelectronics 12 Rue Jules Horowitz Grenoble France GIPSA Lab Grenoble France

ISBN: (纸本)9780819484079

This paper describes an interpolation method that takes into account the edge orientation in order to avoid typical interpolation artifacts (jagging, staircase effects ... ). It is first based on an edge orientation estimation, performed in the wavelet domain. The estimation uses the multi-resolution features of wavelets to give an accurate and non-biased description of the frequency characteristics of the edges, as well as their orientation. The interpolation is then performed, using the edge orientation estimation, to improve a reference interpolation (cubic-spline for instance). This improvement is carried out by filtering the edges with a Gaussian kernel along their direction in order to smooth the contour in the direction parallel to the edge, which avoids disturbing variations across them (jagging and staircase effects). This technique also keeps the sharpness of the transition in the direction perpendicular to the contour to avoid blur. Results are presented on both synthetic and real images, showing the visual impact of the presented method on the quality of interpolated images. Comparisons are made with the usual cubic-spline interpolation, and with other edge-directed interpolation techniques to discuss the choices that have been made in our method.

关键词： Wavelets Gabor filtering Edge Direction image Analysis Multi-resolution image interpolation Upscaling

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image segmentation refinement by modeling in turning function space

Image segmentation refinement by modeling in turning functio...

引用

Conference on image processing: algorithms and systems ix

作者： Volotao, Carlos F. S. Erthal, Guaraci J. Santos, Rafael D. C. Dutra, Luciano V. IME Praca Gen Tiburcio 80 BR-22290270 Rio De Janeiro Brazil Natl Inst Space Res INPE BR-12227 Sao Jose Dos Campos SP Brazil

ISBN: (纸本)9780819484079

This work proposes a different approach for the use of turning function space to change shapes in accordance with shape descriptions and consistent with spectral information. The main steps are: (1) segmentation;(2) contour extraction;(3) turning function space transform;(4) classification;(5) shape analysis;and (6) blob enhancement on image space. In the analysis of shape the boundary is modified based on both image and model and constraints are imposed to portions of the turning function. Shape modeling can be done by defining criteria such as linearity, angles and sizes. Results on synthetic examples are presented.

关键词： object detection polygon simplification tangent angle function shape analysis segmentation snake

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Detection of motion blur direction based on maxima locations for blind deconvolution

Detection of motion blur direction based on maxima locations...

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Conference on image processing: algorithms and systems ix

作者： Chong, Rachel M. Tanaka, Toshihisa Tokyo Univ Agr & Technol Koganei Tokyo 1848588 Japan

ISBN: (纸本)9780819484079

The blurs in images closely resemble an ideal point spread function (PSF) model. This similarity can be exploited in the deconvolution process by learning a model that best fits the estimated PSF. In order to achieve this, a model is selected from the provided training set and then integrated into the reconstruction cost function. In this paper, we propose to eliminate the need for a training set and instead use a reference PSF (RPSF) in its place. This eliminates the need for specifying a training set as well as the dependence on estimated quantities. Furthermore, it is only dependent on the given degraded image assuming that it is uniformly blurred. The method is tested with motion blurs in different directions since it is one of the most commonly encountered problems when using consumer cameras. Using the blur support as a priori knowledge, the results show that the proposed method is capable of accurately determining the motion direction even in the presence of noise. The reconstruction of the image is achieved by using a modified cost function that also accounts for the contour of the estimated PSF. Results show that higher image quality and lower PSF estimation error can be obtained.

关键词： image maxima Hough transform motion blur point spread function blind deconvolution alternating minimization

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Line and streak detection on polished and textured surfaces using line integrals

Line and streak detection on polished and textured surfaces ...

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Conference on image processing: algorithms and systems ix

作者： Erkilinc, M. Sezer Jaber, Mustafa Saber, Eli Pearson, Robert Rochester Inst Technol Dept Elect & Microelect Engn Rochester NY 14623 USA Rochester Inst Technol Chester F Carlson Ctr Imaging Sci Rochester NY 14623 USA

ISBN: (纸本)9780819484079

In this paper, a framework for detecting lines in a polished or textured substrate is proposed. Modules for image capture, rectification, enhancement, and line detection are included. If the surface being examined is specular (mirror-like), the image capture will be restricted, that is, the camera has to be fixed off-axis in the zenith direction. A module for image rectification and projection is included to overcome this limitation in order to yield an orthographic image. In addition, a module for image enhancement that includes high-boost is employed to improve the edge sharpness and decrease the spatial noise in the image. Finally, a line-integral technique is applied to find the confidence vectors that represent the spatial positions of the lines of interest. The Full-Width at Half-Max (FWHM) approximation is applied to determine the corresponding lines in a target image. Experimental results show that our technique has an effective performance on synthetic and real images. Print quality assessment is the main application of the proposed algorithm;however, it can be used to detect lines/streak in prints, on substrate or any type of media where lines are visible.

关键词： line detection line integral image rectification print quality packaging

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Color image lossy compression based on blind evaluation and prediction of noise characteristics

Color image lossy compression based on blind evaluation and ...

引用

Conference on image processing: algorithms and systems ix

作者： Ponomarenko, Nikolay N. Lukin, Vladimir V. Egiazarian, Karen O. Lepisto, Leena Natl Aerosp Univ UA-61070 Kharkov Ukraine Tampere Univ Technol FIN-33101 Tampere Finland Nokia Electr Ltd FIN-33720 Tampere Finland

ISBN: (纸本)9780819484079

The paper deals with JPEG adaptive lossy compression of color images formed by digital cameras. Adaptation to noise characteristics and blur estimated for each given image is carried out. The dominant factor degrading image quality is determined in a blind manner. Characteristics of this dominant factor are then estimated. Finally, a scaling factor that determines quantization steps for default JPEG table is adaptively set (selected). Within this general framework, two possible strategies are considered. A first one presumes blind estimation for an image after all operations in digital image processing chain just before compressing a given raster image. A second strategy is based on prediction of noise and blur parameters from analysis of RAW image under quite general assumptions concerning characteristics parameters of transformations an image will be subject to at further processing stages. The advantages of both strategies are discussed. The first strategy provides more accurate estimation and larger benefit in image compression ratio (CR) compared to super-high quality (SHQ) mode. However, it is more complicated and requires more resources. The second strategy is simpler but less beneficial. The proposed approaches are tested for quite many real life color images acquired by digital cameras and shown to provide more than two time increase of average CR compared to SHQ mode without introducing visible distortions with respect to SHQ compressed images.

关键词： color image lossy compression blind estimation prediction

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PSO-Based Methods for Medical image Registration and Change Assessment of Pigmented Skin

PSO-Based Methods for Medical Image Registration and Change ...

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Conference on image processing: algorithms and systems ix

作者： Kacenjar, Steve Zook, Matthew Balint, Michael Lockheed Martin Corp 6801 Rockledge Dr Bethesda MD 20817 USA Fox Chase Canc Ctr Rockledge PA 19046 USA

ISBN: (纸本)9780819484079

There are various scientific and technological areas in which it is imperative to rapidly detect and quantify changes in imagery over time. In fields such as earth remote sensing, aerospace systems, and medical imaging, searching for time-dependent, regional changes across deformable topographies is complicated by varying camera acquisition geometries, lighting environments, background clutter conditions, and occlusion. Under these constantly-fluctuating conditions, the use of standard, rigid-body registration approaches often fail to provide sufficient fidelity to overlay image scenes together. This is problematic because incorrect assessments of the underlying changes of high-level topography can result in systematic errors in the quantification and classification of interested areas. For example, in the current naked-eye detection strategies of melanoma, a dermatologist often uses static morphological attributes to identify suspicious skin lesions for biopsy. This approach does not incorporate temporal changes which suggest malignant degeneration. By performing the co-registration of time-separated skin imagery, a dermatologist may more effectively detect and identify early morphological changes in pigmented lesions;enabling the physician to detect cancers at an earlier stage resulting in decreased morbidity and mortality. This paper describes an image processing system which will be used to detect changes in the characteristics of skin lesions over time. The proposed system consists of three main functional elements: 1.) coarse alignment of time-sequenced imagery, 2.) refined alignment of local skin topographies, and 3.) assessment of local changes in lesion size. During the coarse alignment process, various approaches can be used to obtain a rough alignment, including: 1.) a manual landmark/ intensity-based registration method(1), and 2.) several flavors of autonomous optical matched filter methods(2). These procedures result in the rough alignment of a patient

关键词： image registration deformable membrane particle swarm optimization PSO melanoma medical image processing

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Multi-seam carving via seamlets

Multi-seam carving via seamlets

引用

Conference on image processing: algorithms and systems ix

作者： Conger, David D. Kumar, Mrityunjay Radha, Hayder Michigan State Univ Dept Elect & Comp Engn WAVES Lab E Lansing MI 48824 USA Eastman Kodak Co Rochester NY 14650 USA

ISBN: (纸本)9780819484079

Seam carving is a powerful retargeting algorithm for mapping images to arbitrary sizes with arbitrary aspect ratios. Meanwhile, the seamlet transform has been introduced as an efficient image representation for seam-carving-based retargeting over heterogeneous multimedia devices with a broad range of display sizes. The original seamlet transform was developed using Haar filters, and hence it enabled traditional single-seam carving by removing a single seam at a time in a recursive manner until the desired image size was reached. In this paper, we develop a more efficient approach for seam carving by enabling multi-seam carving, where at each step of the retargeting algorithm, multiple seams are carved simultaneously. We achieve multi-seam carving by (a) extending the seamlet transform to allow for larger filters, and (b) employing local circular convolution in the vicinity of the selected seams. We show that by extending the seamlet transform we can employ popular filterbanks such as Daubechies' wavelets to achieve efficient multi-seam carving with visual quality that is comparable to single-seam carving using the Haar transform. Furthermore, with multi-seam carving, the number of iterations needed to achieve a given target size can be reduced significantly.

关键词： image resizing retargeting seam carving seamlet transform wavelets discrete wavelet transform

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Unsupervised automated panorama creation for realistic surveillance scenes through weighted mutual information registration

Unsupervised automated panorama creation for realistic surve...

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Conference on image processing: algorithms and systems ix

作者： Keane, Thomas P. Saber, Eli Rhody, Harvey Savakis, Andreas Raj, Jeffrey Rochester Inst Technol Dept Elect & Microelect Engn Rochester NY 14623 USA Rochester Inst Technol Dept Comp Engn Rochester NY 14623 USA Rochester Inst Technol Chester F. Carlson Ctr Imaging Sci Rochester NY 14623 USA UTC Fire & Security Co Lenel Syst Int Inc Pittsford NY 14534 USA

ISBN: (纸本)9780819484079

Automated panorama creation usually requires camera calibration or extensive knowledge of camera locations and relations to each other. Registration problems are often solved by these same camera parameters or the result of complex point matching schemes. This paper presents a novel automated panorama creation algorithm by using an affine transformation search based on maximized mutual information (MMI). MMI techniques are often limited to airborne and satellite imagery or medical images, but we can show that a simple MMI algorithm very well approximates realistic scenes of varying depth distortion. This study was performed on stationary color surveillance video cameras and proves extremely worthwhile in any system with limited or no a priori camera-to-camera parameters. This algorithm is quite robust on a very large range of strict- to nearly-affine related scenes, and provides a great approximation for the overlap regions in scenes related by a projective homography. Practical considerations were surprisingly significant in molding the development of this robust and versatile algorithm.

关键词： image Registration Surveillance Video processing Mutual Information

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Spatio-temporal analysis and forward modeling of solar polar plumes in white light

Spatio-temporal analysis and forward modeling of solar polar...

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Conference on image processing: algorithms and systems ix

作者： Llebaria, A. Morillot, O. Boursier, Y. Lamy, P. CNRS LAM OAMP BP8 F-13376 Marseille 12 France Ctr Phys Particules Marseille F-13288 Marseille France

ISBN: (纸本)9780819484079

The analysis of the data provided by the LASCO/C2 coronagraph on board the SOHO spatial observatory revealed the fractal characteristics of many remarkable structures of the solar corona forming the solar atmosphere. A multiscale analysis of recent image sequences has brought a clearer view of the evolution and the local structure of these features which results from a two steps projection process of the 2D electron distribution over the Sun polar caps. To get an insight in the volume density distribution over these caps and their evolution within time, we used the forward modeling approach based on the present knowledge about the plasma distribution, the physical process of diffusion and the projection geometry on the field of view. The analysis provides us with the multifractal characterization of the observed phenomena. In the forward modeling process the goal is to reconstruct the time sequence of 2D electronic distributions slowly evolving over the Sun polar caps. We used different methodologies: the inverse Fourier transform of 2D+1D (surface and time) frequency modeling, the evolving multiscale synthesis with Gaussian wavelets and the concealed Markov approach. Finaly, a procedure derived from the Voss generation scheme of fBm (fractal Brownian motion) fractals has been successfully developped. These different methods are compared and their relative advantages and drawbacks discussed.

关键词： Fractal analysis Coronagraphy Sun image processing Solar processes Diffusion Plasma image analysis Observatories Process modeling

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