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2009 International Workshop on Local and Non-Local Approximation in Image Processing最新文献

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Entropic segmentation by region growing and merging for drop shape analysis 基于区域增长与融合的水滴形态熵分割
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278396
J. F. Gómez-Lopera, P. Luque-Escamilla, J. Martínez-Aroza, R. Román-Roldán, M. Cabrerizo-Vílchez, M. Rodríguez-Valverde, F. J. Montes-Ruíz-Cabello
{"title":"Entropic segmentation by region growing and merging for drop shape analysis","authors":"J. F. Gómez-Lopera, P. Luque-Escamilla, J. Martínez-Aroza, R. Román-Roldán, M. Cabrerizo-Vílchez, M. Rodríguez-Valverde, F. J. Montes-Ruíz-Cabello","doi":"10.1109/LNLA.2009.5278396","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278396","url":null,"abstract":"A new approach to image segmentation based on entropic region growing and merging, which is useful in drop shape analysis, is presented in this paper. The procedure works in three steps. First, a normalized divergence matrix is obtained which gives the likelihood of being a boundary pixel for each pixel in the image. Second, a region growing algorithm is carried out on the divergence matrix, keeping a record of boundaries between adjacent regions. Third, some regions are merged by following a combined entropic criterion, based on both the divergences of the matrix along the common boundary and the global divergence between two adjacent regions. The final contour is adapted by a dynamical spline fitting. This general purpose algorithm is presented here applied to drop shape analysis.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127976825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Methods for local phase quantization in blur-insensitive image analysis 模糊不敏感图像分析中的局部相位量化方法
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278397
J. Heikkila, Ville Ojansivu
{"title":"Methods for local phase quantization in blur-insensitive image analysis","authors":"J. Heikkila, Ville Ojansivu","doi":"10.1109/LNLA.2009.5278397","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278397","url":null,"abstract":"Image quality is often degraded by blur caused by, for example, misfocused optics or camera motion. Blurring may also deteriorate the performance of computer vision algorithms if the image features computed are sensitive to these degradations. In this paper, we present an image descriptor based on local phase quantization that is robust to centrally symmetric blur. The descriptor referred to as local phase quantization (LPQ) can be used to characterize the underlying image texture. We also present a decorrelation scheme and propose three approaches for extracting the local phase information. Different combinations of them result in totally six variants of the operator that can be used alternatively. We show experimentally that these operators have slightly varying performance under different blurring conditions. In all test cases, including also sharp images, the new descriptors can outperform two state-of-the-art methods, namely, local binary pattern (LBP) and a method based on Gabor filter banks.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116321667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 41
Noise variance estimation in nonlocal transform domain 非局部变换域的噪声方差估计
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278404
Aram Danielyan, A. Foi
{"title":"Noise variance estimation in nonlocal transform domain","authors":"Aram Danielyan, A. Foi","doi":"10.1109/LNLA.2009.5278404","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278404","url":null,"abstract":"We consider the estimation of the variance of an additive white Gaussian noise corrupting an image.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125078708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 51
Quality assessment measure based on image structural properties 基于图像结构特性的质量评价方法
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278400
D. Asatryan, K. Egiazarian
{"title":"Quality assessment measure based on image structural properties","authors":"D. Asatryan, K. Egiazarian","doi":"10.1109/LNLA.2009.5278400","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278400","url":null,"abstract":"In this paper, a new objective quality assessment measure for images is proposed based on statistical structural image analysis using Weibull model and Cramer-von Mises statistics. It is estimated via proximity of parameters of empirical distributions of a gradient magnitude of pixel intensities. Results of numerical experiments demonstrate that the proposed measure is more adequate to perception by human visual system than the usual pixel-by-pixel measures. Unlike other quality assessment measures, a new one can be used on not well-aligned images or on images having different sizes.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127543776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 22
On the inversion of the Anscombe transformation in low-count Poisson image denoising 低计数泊松图像去噪中Anscombe变换的反演
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278406
Markku Makitalo, A. Foi
{"title":"On the inversion of the Anscombe transformation in low-count Poisson image denoising","authors":"Markku Makitalo, A. Foi","doi":"10.1109/LNLA.2009.5278406","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278406","url":null,"abstract":"The removal of Poisson noise is often performed through the following three-step procedure. First, the noise variance is stabilized by applying the Anscombe root transformation to the data, producing a signal in which the noise can be treated as additive Gaussian noise with unitary variance. Second, the noise is removed using a conventional denoising algorithm for additive white Gaussian noise. Third, an inverse transformation is applied to the denoised signal, obtaining the estimate of the signal of interest. The choice of the proper inverse transformation is crucial in order to minimize the bias error which arises when the nonlinear forward transformation is applied. We present an experimental analysis using a few state-of-the-art denoising algorithms and show that the estimation can be consitently improved by applying the exact unbiased inverse, particularly at the low-count regime.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131041680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 24
A note on multi-image denoising 关于多图像去噪的注意事项
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278408
Toni Buades, Y. Lou, J. Morel, Zhongwei Tang
{"title":"A note on multi-image denoising","authors":"Toni Buades, Y. Lou, J. Morel, Zhongwei Tang","doi":"10.1109/LNLA.2009.5278408","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278408","url":null,"abstract":"Taking photographs under low light conditions with a hand-held camera is problematic. A long exposure time can cause motion blur due to the camera shaking and a short exposure time gives a noisy image. We consider the new technical possibility offered by cameras that take image bursts. Each image of the burst is sharp but noisy. In this preliminary investigation, we explore a strategy to efficiently denoise multi-images or video. The proposed algorithm is a complex image processing chain involving accurate registration, video equalization, noise estimation and the use of state-of-the-art denoising methods. Yet, we show that this complex chain may become risk free thanks to a key feature: the noise model can be estimated accurately from the image burst. Preliminary tests will be presented. On the technical side, the method can already be used to estimate a non parametric camera noise model from any image burst.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116715639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 98
Coupled multi-frame super-resolution with diffusive motion model and total variation regularization 耦合多帧超分辨扩散运动模型和全变分正则化
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278403
Mehran Ebrahimi, E. Vrscay, Anne L. Martel
{"title":"Coupled multi-frame super-resolution with diffusive motion model and total variation regularization","authors":"Mehran Ebrahimi, E. Vrscay, Anne L. Martel","doi":"10.1109/LNLA.2009.5278403","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278403","url":null,"abstract":"The problem of recovering a high-resolution image from a set of distorted (e.g., warped, blurred, noisy) and low-resolution images is known as super-resolution. Accurate motion estimation from low-resolution measurements is a fundamental challenge of the super-resolution problem. Some recent promising advances in this area have been focused on coupling or combing the super-resolution reconstruction and the motion estimation. However, the existing approaches are limited to parametric motion models, e.g., affine transformations. In this paper, we shall address the coupled super-resolution problem with a non-parametric motion model. We then consider a variational formulation of the problem and use a PDE-approach to construct a numerical scheme for its solution. In this paper, diffusion regularization is used for the motion model and total variation regularization for the super-resolved image.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114668047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Red eye detection using color and shape 使用颜色和形状进行红眼检测
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278391
L. Lepisto, A. Launiainen, I. Kunttu
{"title":"Red eye detection using color and shape","authors":"L. Lepisto, A. Launiainen, I. Kunttu","doi":"10.1109/LNLA.2009.5278391","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278391","url":null,"abstract":"Red eye artifact caused by flash is a common problem in consumer photography. The artifact can be avoided by certain flash techniques, but the use of image processing algorithms has proved to be an efficient approach for the detection and correction of the red eyes in the images. In this paper, we present a novel method for an automatic detection of red eyes in the image. The method is based on the localization of red regions in the image, after which the special character of each candidate region is inspected based on shape analysis. Once the candidate regions have been detected, they are classified into red eyes and other regions based on specific classification rules. In the experiments, a wide set of digital photographs containing red eyes in different conditions and circumstances have been used. The results reveal that the method is able to detect relatively accurately the red eyes in the images, and it provides robustness and fastness required in the mobile devices. Also the rate of false positive detections is low.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122846084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Efficient design of a low redundant Discrete Shearlet Transform 低冗余离散Shearlet变换的高效设计
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278394
B. Goossens, J. Aelterman, H. Luong, A. Pižurica, W. Philips
{"title":"Efficient design of a low redundant Discrete Shearlet Transform","authors":"B. Goossens, J. Aelterman, H. Luong, A. Pižurica, W. Philips","doi":"10.1109/LNLA.2009.5278394","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278394","url":null,"abstract":"Recently, there has been a huge interest in multiresolution representations that also perform a multidirectional analysis. The Shearlet transform provides both a multiresolution analysis (such as the wavelet transform), and at the same time an optimally sparse image-independent representation for images containing edges. Existing discrete implementations of the Shearlet transform havemainly focused on specific applications, such as edge detection or denoising, and were not designed with a low redundancy in mind (the redundancy factor is typically larger than the number of orientation subbands in the finest scale). In this paper, we present a novel design of a Discrete Shearlet Transform, that can have a redundancy factor of 2.6, independent of the number of orientation subbands, and that has many interesting properties, such as shift-invariance and self-invertability. This transform can be used in a wide range of applications. Experiments are provided to show the improved characteristics of the transform.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130343372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 32
Nonlocal image deblurring: Variational formulation with nonlocal collaborative L0-norm prior 非局部图像去模糊:具有非局部协同l0范数先验的变分公式
2009 International Workshop on Local and Non-Local Approximation in Image Processing Pub Date : 2009-10-06 DOI: 10.1109/LNLA.2009.5278405
V. Katkovnik, K. Egiazarian
{"title":"Nonlocal image deblurring: Variational formulation with nonlocal collaborative L0-norm prior","authors":"V. Katkovnik, K. Egiazarian","doi":"10.1109/LNLA.2009.5278405","DOIUrl":"https://doi.org/10.1109/LNLA.2009.5278405","url":null,"abstract":"Spatially adaptive nonlocal patch-wise estimation is one of the most promising recent directions in image processing. Within this framework a set of the state-of-the-art Block Matching 3-D (BM3D) algorithms has been developed for different imaging problems [1]–[5]. Recently, a special prior hoas been proposed allowing to reformulate the multi-state hard-thresholding BM3D denoising as global minimization of an energy criterion [6]. The out-standing performance of BM3D works as a strong argument in favor of this prior giving an efficient multilayer redundant image model. The variational formulation is used in [6] in order to design a novel recursive denoising algorithm. In this paper the nonlocal collaborative l0-norm prior is a tool to design deblurring algorithms, where the global penalty function works as an adaptive regularizator. The main contribution concerns the development and testing of algebraic and frequency domain recursive algorithms minimizing the global criterion. Simulation demonstrate a very good performance of the novel algorithms.","PeriodicalId":231766,"journal":{"name":"2009 International Workshop on Local and Non-Local Approximation in Image Processing","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116105316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 7
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