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Graph cut and image intensity-based splitting improves nuclei segmentation in high-content screening

Graph cut and image intensity-based splitting improves nucle...

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Conference on image processing - algorithms and systems xi

作者： Farhan, Muhammad Ruusuvuori, Pekka Emmenlauer, Mario Raemoe, Pauli Yli-Harja, Olli Dehio, Christoph Tampere Univ Technol Dept Signal Proc FIN-33101 Tampere Finland

ISBN: (纸本)9780819494283

Quantification of phenotypes in high-content screening experiments depends on the accuracy of single cell analysis. In such analysis workflows, cell nuclei segmentation is typically the first step and is followed by cell body segmentation, feature extraction, and subsequent data analysis workflows. Therefore, it is of utmost importance that the first steps of high-content analysis are done accurately in order to guarantee correctness of the final analysis results. In this paper, we present a novel cell nuclei image segmentation framework which exploits robustness of graph cut to obtain initial segmentation for image intensity-based clump splitting method to deliver the accurate overall segmentation. By using quantitative benchmarks and qualitative comparison with real images from high-content screening experiments with complicated multinucleate cells, we show that our method outperforms other state-of-the-art nuclei segmentation methods. Moreover, we provide a modular and easy-to-use implementation of the method for a widely used platform.

关键词： High-content screening image segmentation Graph cut Concavity point analysis Clump splitting

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HDR image multi-bit watermarking using bilateral-filtering-based masking

HDR image multi-bit watermarking using bilateral-filtering-b...

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Conference on image processing - algorithms and systems xi

作者： Solachidis, Vassilis Maiorana, Emanuele Campisi, Patrizio Univ Roma Tre Dept Appl Elect I-00146 Rome Italy

ISBN: (纸本)9780819494283

The present paper proposes a blind multi-bit watermarking method for High Dynamic Range (HDR) images. The proposed approach is designed in order to guarantee the watermark imperceptibility both in the HDR marked image and in its Low Dynamic Range (LDR) counterpart, being thus robust against significant non-linear distortions such as those performed by tone-mapping operators (TMOs). In order to do so, the wavelet transform of the Just Noticeable Difference (JND)-scaled space of the original HDR image is employed as embedding domain Moreover, a visual mask taking into account specific aspects of the Human Visual System (HVS) is exploited to improve the quality of the resulting watermarked image. Specifically, bilateral filtering is used to locate information on the detail part of the HDR image, where the watermark should be preferably embedded. A contrast sensitivity function is also employed to modulate the watermark intensity in each wavelet decomposition subband according to its scale and orientation. An extensive set of experimental results testifies the effectiveness of the proposed scheme in embedding multi-bit watermarks into HDR images without affecting the visual quality of the original image, while being robust against TMOs.

关键词： high dynamic range imaging watermarking bilateral filtering tone-mapping operators

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Quality constraint and rate-distortion optimization for predictive image coders

Quality constraint and rate-distortion optimization for pred...

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Conference on image processing - algorithms and systems xi

作者： Samrouth, Khouloud Pasteau, Francois Deforges, Olivier CNRS UMR 6164 IETR Lab Rennes France

ISBN: (纸本)9780819494283

Next generations of image and video coding methods should of course be efficient in terms of compression, but also propose advanced functionalities. Among these functionalities such as scalability, lossy and lossless coding, data protection, Rate Distortion Optimization (RDO) and Rate Control (RC) are key issues. RDO aims at optimizing compression performances, while RC mechanism enables to exactly compress at a given rate. A less common functionality than RC, but certainly more helpful, is Quality Control (QC): the constraint is here given by the quality. In this paper, we introduce a joint solution for RDO and QC applied to a still image codec called Locally Adaptive Resolution (LAR), providing scalability both in resolution and SNR and based on a multi-resolution structure. The technique does not require any additional encoding pass. It relies on a modeling and estimation of the prediction errors obtained in an early work. First, quality constraint is applied and propagated through the whole resolution levels called pyramid. Then, the quantization parameters are deduced considering inter and intra pyramid level relationships. Results show that performances of the proposed method are very close to an exhaustive search solution.

关键词： Predictive Coder quantization quality allocation rate-distortion optimization

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Target Re-Identification in Low Quality Camera Networks

Target Re-Identification in Low Quality Camera Networks

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Conference on image processing - algorithms and systems xi

作者： Battisti, Federica Carli, Marco Farinella, Giovanna Neri, Alessandro Univ Roma TRE Dept Appl Elect Rome Italy

ISBN: (纸本)9780819494283

Person re-identification through a camera network deals with finding a correct link between consecutive observations of the same target among different cameras in order to choose the most probable correspondence among a set of possible matches. This task is particularly challenging in presence of low-resolution camera networks. In this work, a method for people re-identification in a framework of low-resolution camera network is presented. The proposed approach can be divided in two parts. First, the illumination changes of a target while crossing the network is analyzed. The color structure is evaluated using a novel color descriptor, the Color Structure Descriptor, which describes the differences of dominant colors between two regions of interest. Afterwards, a new pruning system for the links, the Target Color Structure is proposed. Results shows that the improvements achieved applying Target Color Structure control are up to 4% for the top rank and up to 16% considering the first eleven more similar candidates.

关键词： Video Surveillance Person Identification Context Histograms image color analysis

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Improved Multi Channel Up-Sampling Method for Reconstruction Based Super-Resolution

Improved Multi Channel Up-Sampling Method for Reconstruction...

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Conference on image processing - algorithms and systems xi

作者： Jee, Seung Hoon Kang, Moon Gi Yonsei Univ Inst TMS Informat Technol Seoul 120749 South Korea

ISBN: (纸本)9780819494283

In reconstruction based super-resolution, it is an important issue to up-sample and to merge the high-frequency information contained in low-resolution images efficiently and without artifact. The conventional up-sampling methods, which used for registering low-resolution data to high-resolution grid, have the difference between them and ideal up-sampling in observation modeling. In this paper, we analyze the difference and propose a new up-sampling and merging method which is able to incorporate low-resolution images without loss of the high frequency data and minimizes the artifact caused by data insufficiency. By this method, regions that the registered high frequency data do not cover are naturally regularized without using complex regularizers. The experimental results show that the choice of up-sampling significantly affects the quality of resulting images and the proposed up-sampling method gives better results compared with conventional simple up-sampling method.

关键词： Super-Resolution image Reconstruction Interpolation Up-sampling Multi Frame

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Locally Tuned Inverse Sine Nonlinear Technique for Color image Enhancement

Locally Tuned Inverse Sine Nonlinear Technique for Color Ima...

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Conference on image processing - algorithms and systems xi

作者： Arigela, Saibabu Asari, Vijayan K. Univ Dayton Dept Elect & Comp Engn Dayton OH 45419 USA

ISBN: (纸本)9780819494283

In this paper, a novel inverse sine nonlinear transformation based image enhancement technique is proposed to improve the visual quality of images captured in extreme lighting conditions. This method is adaptive, local and simple. The proposed technique consists of four main stages namely histogram adjustment, dynamic range compression, contrast enhancement and nonlinear color restoration. Histogram adjustment on each spectral band is performed to belittle the effect of illumination. Dynamic range compression is accomplished by an inverse sine nonlinear function with a locally tunable image dependent parameter based on the local statistics of each pixel's neighborhood regions of the luminance image. A nonlinear color restoration process based on the chromatic information and luminance of the original image is employed. A statistical quantitative evaluation is performed with the state of the art techniques to analyze and compare the performance of the proposed technique. The proposed technique is also tested on face detection in complex lighting conditions. The results of this technique on images captured in hazy/foggy weather environment are also presented. The evaluation results confirm that the proposed method can be applied to surveillance, security applications in complex lighting environments.

关键词： dynamic range compression inverse sine nonlinearity nonlinear transformation local contrast enhancement nonlinear color restoration face detection

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Parallel algorithms for fast subpixel detection in hyperspectral imagery

Parallel algorithms for fast subpixel detection in hyperspec...

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Conference on image processing - algorithms and systems xi

作者： Wong, Chung M. Shepanski, John Sandor-Leahy, Stephanie Northrop Grumman Aerosp Syst Redondo Beach CA 90278 USA

ISBN: (纸本)9780819494283

We present parallel algorithms for fast subpixel detection of targets in hyperspectral imagery produced by our Hyperspectral Airborne Tactical Instrument (HATI-2500). The HATI-2500 hyperspectral imaging system has a blue-enhanced visible-near-IR (VNIR) and a full short-wave IR (SWIR) range response from 400 to 2500 nm. It has an industry-leading spectral resolution that ranges from 6 nm down to 1.5 nm in the VNIR region. The parallel detection algorithm selected for processing the hyperspectral data cubes is based on the adaptive coherence/cosine estimator (ACE). The ACE detector is a robust detector that is built upon the theory of generalized likelihood ratio testing (GLRT) in implementing the matched subspace detector to unknown parameters such as the noise covariance matrix. Subspace detectors involve projection transformations whose matrices can be efficiently manipulated through multithreaded massively parallel processors on modern graphics processing units (GPU). The GPU kernels developed in this work are based on the CUDA computing architecture. We constrain the detection problem to a model with known target spectral features and unstructured background. The processing includes the following steps: 1) scale and offset applied to convert the data from digital numbers to radiance values, 2) update the background inverse covariance estimate in a line-by-line manner, and 3) apply the ACE detector for each pixel for binary hypothesis testing. As expected, the algorithm is extremely effective for homogeneous background, such as open desert areas;and less effective in mixed spectral regions, such as those over urban areas. The processing rate is shown to be faster than the maximum frame rate of the camera (100 Hz) with a comfortable margin.

关键词： Hyperspectral imaging remote sensing real-time processing parallel computing

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Fast texture and structure image reconstruction using the perceptual hash

Fast texture and structure image reconstruction using the pe...

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Conference on image processing - algorithms and systems xi

作者： Voronin, V. V. Marchuk, V. I. Frantc, V. A. Egiazarian, K. O. Don State Tech Univ Dept Radioelect Syst Shakhty 346500 Russia

ISBN: (纸本)9780819494283

This paper focuses on the fast texture and structure reconstruction of images. The proposed method, applied to images, consists of several steps. The first one deals with the extracted textural features of the input images based on the Law's energy. The pixels around damaged image regions are clustered using these features, that allow to define the correspondence between pixels from different patches. Second, cubic spline curve is applied to reconstruct a structure and to connect edges and contours in the damaged area. The choice of the current pixel to be recovered is decided using the fast marching approach The Telea method or modifications of the exemplar based method are used after this depending on the classification of the regions where to-be-restored pixel is located. In modification to quickly find patches we use the perceptual hash. Such a strategy allows to get some data structure containing the hashes of similar patches. This enables us to reduce the search procedure to the procedure for "calculations" of the patch The proposed method is tested on various samples of images, with different geometrical features and compared with the state-of-the-art image inpainting methods;the proposed technique is shown to produce better results in reconstruction of missing small and large objects on test images.

关键词： image inpainting spline interpolation perceptual hash edge reconstruction texture synthesis

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A GPU based implementation of Direct Multi-bit Search (DMS) screen algorithm

A GPU based implementation of Direct Multi-bit Search (DMS) ...

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Conference on image processing - algorithms and systems xi

作者： Trager, Barry Chandu, Kartheek Wu, Chai Wah Stanich, Mikel Ricoh Prod Print Solut LLC Boulder CO 80301 USA

ISBN: (纸本)9780819494283

In this paper, we study the feasibility for using programmable Graphics processing Unit (GPU) technology for image halftoning, in particular implementing the computationally intense Direct Multi-bit Search (DMS) Screen algorithm. Multi-bit screening is an extension of binary screening, in which every pixel in continuoustone image can be rendered to one among multiple output states. For example, a 2 bit printer is capable of printing with four different drop sizes. In our previous work, we have extended the Direct Binary Search (DBS) to the multi-bit case using Direct Multi-bit Search (DMS) where at every pixel the algorithm chooses the best drop output state to create a visually pleasing halftone pattern without any user de fined guidance. This process is repeated throughout the entire range of gray levels while satisfying the stacking constraint to create a high quality multi-bit screen (dither mask). In this paper, we illustrate how employing Graphics processing Units (GPU) can speed-up intensive DMS image processing operations. Particularly, we illustrate how different modules can be been parallelized. The main goal of many of the previous articles regarding DBS is to decrease the execution time of the algorithm. One of the most common approaches is to decrease the neighborhood size or filter size. The proposed parallel approach allows us to use a large neighborhood and filter size, to achieve the highest halftone quality, while having minimal impact on performance. In addition, we also demonstrate processing several non-overlapping neighborhoods in parallel, by utilizing the GPU's parallel architecture, to further improve the computational efficiency.

关键词： Halftoning Direct Multi-bit Search (DMS) GPU Computing Parallel processing Screening

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Vasculature segmentation using parallel multi-hypothesis template tracking on heterogeneous platforms

Vasculature segmentation using parallel multi-hypothesis tem...

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Conference on image processing - algorithms and systems xi

作者： Zhang, Dong Ping Howes, Lee Adv Micro Devices Inc Res Grp Sunnyvale CA 94088 USA

ISBN: (纸本)9780819494283

We present a parallel multi-hypothesis template tracking algorithm on heterogeneous platforms using a layered dispatch programming model. The contributions of this work are: an architecture-specific optimised solution for vasculature structure enhancement, an approach to segment the vascular lumen network from volumetric CTA images and a layered dispatch programming model to free the developers from hand-crafting mappings to particularly constrained execution domains on high throughput architecture. This abstraction is demonstrated through a vasculature segmentation application and can also be applied in other real-world applications. Current GPGPU programming models define a grouping concept which may lead to poorly scoped local/shared memory regions and an inconvenient approach to projecting complicated iterations spaces. To improve on this situation, we propose a simpler and more flexible programming model that leads to easier computation projections and hence a more convenient mapping of the same algorithm to a wide range of architectures. We first present an optimised image enhancement solution step-by-step, then solve a separable nonlinear least squares problem using a parallel Levenberg-Marquardt algorithm for template matching, and perform the energy efficiency analysis and performance comparison on a variety of platforms, including multi-core CPUs, discrete GPUs and APUs. We propose and discuss the efficiency of a layered-dispatch programming abstraction for mapping algorithms onto heterogeneous architectures.

关键词： image Enhancement Cardiac Imaging GPU computing Programming Model

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