2009 Digital Image Computing: Techniques and Applications最新文献_第3页

Automatic Tuning of MST Segmentation of Mammograms for Registration and Mass Detection Algorithms 用于配准和质量检测算法的乳房x光片MST分割的自动调整

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.72

M. Bajger, Fei Ma, M. Bottema

引用次数: 17

A Direct Method to Self-Calibrate a Surveillance Camera by Observing a Walking Pedestrian 一种通过观察行走的行人对监控摄像机进行自标定的直接方法

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.49

Worapan Kusakunniran, Hongdong Li, Jian Zhang

引用次数: 23

Perspective Invariant Angle Ordering 透视不变角度排序

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.50

David Shaw, N. Barnes

引用次数: 0

Extraction of Road Lanes from High-Resolution Stereo Aerial Imagery Based on Maximum Likelihood Segmentation and Texture Enhancement 基于最大似然分割和纹理增强的高分辨率立体航空影像道路车道提取

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.52

Hang Jin, Yanming Feng, Zhengrong Li

{"title":"Extraction of Road Lanes from High-Resolution Stereo Aerial Imagery Based on Maximum Likelihood Segmentation and Texture Enhancement","authors":"Hang Jin, Yanming Feng, Zhengrong Li","doi":"10.1109/DICTA.2009.52","DOIUrl":"https://doi.org/10.1109/DICTA.2009.52","url":null,"abstract":"Accurate road lane information is crucial for advanced vehicle navigation and safety applications. With the increasing of very high resolution (VHR) imagery of astonishing quality provided by digital airborne sources, it will greatly facilitate the data acquisition and also significantly reduce the cost of data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lanes from aerial images with employment of the image analysis procedures. This algorithm starts with constructing the (Digital Surface Model) DSM and true orthophotos from the stereo images. Next, a maximum likelihood clustering algorithm is used to separate road from other ground objects. After the detection of road surface, the road traffic and lane lines are further detected using texture enhancement and morphological operations. Finally, the generated road network is evaluated to test the performance of the proposed approach, in which the datasets provided by Queensland department of Main Roads are used. The experiment result proves the effectiveness of our approach.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116349675","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: 10

Novel Hardware Algorithms for Row-Parallel Integral Image Calculation 行并行积分图像计算的新硬件算法

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.20

Shoaib Ehsan, A. Clark, K. Mcdonald-Maier

引用次数: 10

Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control 使用不对称增益控制的生物启发对比度增强

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.75

Asim A. Khwaja, Roland Göcke

{"title":"Biologically Inspired Contrast Enhancement Using Asymmetric Gain Control","authors":"Asim A. Khwaja, Roland Göcke","doi":"10.1109/DICTA.2009.75","DOIUrl":"https://doi.org/10.1109/DICTA.2009.75","url":null,"abstract":"A neuro-physiologically inspired model is presented for the contrast enhancement of images. The contrast of an image is calculated using simulated on- and off-centre receptive fields whereby obtaining the corresponding two contrast maps. We propose an adaptive asymmetric gain control function that is applied to the two contrast maps which are then used to reconstruct the image resulting in its contrast enhancement. The image's mean luminance can be adjusted as desired by adjusting the asymmetricity between the gain control factors of the two maps. The model performs local contrast enhancement in the contrast domain of an image where it lends itself very naturally to such adjustments. Furthermore, the model is extended on to colour images using the concept of colour-opponent receptive fields found in the human visual system. The colour model enhances the contrast right in the colour space without extracting the luminance information from it. Being neuro-physiologically plausible, this model can be beneficial in theorising and understanding the gain control mechanisms in the primate visual system. We compare our results with the CLAHE algorithm.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126862816","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: 1

Regularized Multinomial Regression Method for Hyperspectral Data Classification via Pathwise Coordinate Optimization 基于路径坐标优化的正则化多项式回归高光谱数据分类方法

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.89

Jiming Li, Y. Qian

{"title":"Regularized Multinomial Regression Method for Hyperspectral Data Classification via Pathwise Coordinate Optimization","authors":"Jiming Li, Y. Qian","doi":"10.1109/DICTA.2009.89","DOIUrl":"https://doi.org/10.1109/DICTA.2009.89","url":null,"abstract":"Hyperspectral imagery generally contains enormous amounts of data due to hundreds of spectral bands. As recent researchers have discovered, many of the bands are highly correlated and may provide redundant information for the classification related problems. Therefore, feature selection is very important in hyperspectral image processing problem. ''Pathwise Coordinate Descent'' algorithm is the ''one-at-a-time'' coordinate-wise descent algorithm for a class of convex optimization problems. When applied on the L1-regularized regression (lasso) problem, the algorithm can handle large problems and can also efficiently obtain sparse features in a comparatively very low timing cost. Through computing the solutions for a decreasing sequence of regularization parameters, the algorithm also combines model selection procedure into itself. In this paper, we utilize the multinomial logistic regression with lasso, elastic-net convex penalties on hyperspectral image classification. Pathwise Coordinate Descent is used for estimation these models. Experimental results demonstrate that, in the context of the hyperspectral data classification problem, models obtained by Pathwise Coordinate Descent algorithm do effectively achieve a sparse feature subsets and very good classification results with very low computational costs.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123400656","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: 8

Blotch Detection in Pigmented Skin Lesions Using Fuzzy Co-clustering and Texture Segmentation 基于模糊共聚类和纹理分割的色斑检测

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.15

V. Madasu, B. Lovell

引用次数: 26

Affine-Invariant Image Watermarking Using the Hyperbolic Chirp 利用双曲啁啾进行仿射不变图像水印

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.12

P. Fletcher, K. Larkin, S. J. Hardy

引用次数: 2

A Shape-Based Vector Watermark for Digital Mapping 一种基于形状的数字映射矢量水印

2009 Digital Image Computing: Techniques and Applications Pub Date : 2009-12-01 DOI: 10.1109/DICTA.2009.78

S. Bird, C. Bellman, R. V. Schyndel

引用次数: 8