2011 International Conference on Image Information Processing最新文献_第9页

Image fusion using hierarchical PCA. 基于层次PCA的图像融合。

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108966

Ujwala Patil, Uma Mudengudi

{"title":"Image fusion using hierarchical PCA.","authors":"Ujwala Patil, Uma Mudengudi","doi":"10.1109/ICIIP.2011.6108966","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108966","url":null,"abstract":"In this paper we propose image fusion algorithm using hierarchical PCA. Image fusion is a process of combining two or more images (which are registered) of the same scene to get the more informative image. Hierarchical multiscale and multiresolution image processing techniques, pyramid decomposition are the basis for the majority of image fusion algorithms. Principal component analysis (PCA) is a well-known scheme for feature extraction and dimension reduction and is used for image fusion. We propose image fusion algorithm by combining pyramid and PCA techniques and carryout the quality analysis of proposed fusion algorithm without reference image. There is an increasing need for the quality analysis of the fusion algorithms as fusion algorithms are data set dependent. Subjective analysis of fusion algorithm using hierarchical PCA is done by considering the opinion of experts and non experts and for quantitative quality analysis we use different quality metrics. We demonstrate fusion using pyramid, wavelet and PCA fusion techniques and carry out performance analysis for these four fusion methods using different quality measures for variety of data sets and show that proposed image fusion using hierarchical PCA is better for the fusion of multimodal imaged. Visible inspection with quality parameters are used to arrive at a fusion results.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131691404","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: 120

Non-metrical scene reconstruction using a quasi-calibrated prime lens based camera 基于准校准定焦镜头的相机非对称场景重建

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108929

R. Senthilnathan, R. Sivaramakrishnan

{"title":"Non-metrical scene reconstruction using a quasi-calibrated prime lens based camera","authors":"R. Senthilnathan, R. Sivaramakrishnan","doi":"10.1109/ICIIP.2011.6108929","DOIUrl":"https://doi.org/10.1109/ICIIP.2011.6108929","url":null,"abstract":"Three dimensional (3-D) vision techniques in the field of Computer Vision aims mainly at reconstructing a scene to find its three dimensional geometrical information. Passive 3-D vision techniques such as computational stereo vision method do surface reconstruction from disparities arising in images of the same scene taken from multiple views. For reconstruction leading to metrical information of the 3-D geometry of the scene the camera pose with respect to some world reference frame and the camera parameters such as the focal length, sensor size has to be accurately known. Such information especially the pose of the camera might not be known in many applications such as in agricultural, under-water explorations since a unique universal frame of reference is not possible. Also the constancy of the internal camera parameters will not be valid in many applications requiring good accuracy in reconstruction. In such cases the cameras used for passive triangulation is said to be un-calibrated. Stereo vision technique generally requires two images and which need not be from two different cameras. The paper is an attempt to use a single moving camera with which the image of the same scene is acquired from two different views. Since the scene geometry and the pose of the camera are unknown the problem to be addressed is close the so called Structure from Motion (SfM) problem in Computer Vision. The reconstruction method developed in the paper is extended further to segment top surfaces of cuboid shaped objects considered as the objects of interest in the scene reconstruction process. Though the information in the case considered is non-metrical the applications that pose such un-calibrated camera as a demand are plenty.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134644626","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

Disparity estimation using fractional dual tree complex wavelet transform 基于分数对偶树复小波变换的视差估计

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108942

Sanoj Kumar, Sanjeev Kumar, N. Sukavanam, B. Raman

引用次数: 0

Dual watermarking based on Multiple parameter fractional Fourier transform and LSB technique 基于多参数分数傅里叶变换和LSB技术的双水印

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108846

Sudhir Keshari, S. G. Modani

引用次数: 10

A fast 3D reconstruction of inextensible surfaces using adaptive weights 一种基于自适应权值的不可扩展曲面快速三维重构方法

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108946

Arsalan Dezhkam, S. Kasaei

引用次数: 0

Modified PPPE architecture for two-dimensional Radon Transform computation 二维Radon变换计算的改进PPPE结构

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108844

Baljit Kaur, M. Majumder

引用次数: 1

Retinal nerve fibre layer detection in fundus camera images compared to results from optical coherence tomography 眼底相机图像中视网膜神经纤维层检测与光学相干断层扫描结果的比较

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108883

J. Gazárek, J. Jan, R. Kolář, J. Odstrcilík

引用次数: 9

Generating realtime panorama using a generalized feature vector approach 使用广义特征向量方法生成实时全景图

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108878

J. Bhattacharya, S. Majumder, G. Sanyal

引用次数: 1

Fourier shape-frequency words for actions 动作的傅里叶形状频率词

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108939

Bishwajit Sharma, K. Venkatesh, A. Mukerjee

引用次数: 1

Performance of non-coherent signal detection of mary frequency-shift keying in triple layer Wireless Sensor Networks 三层无线传感器网络中多频移键控的非相干信号检测性能

2011 International Conference on Image Information Processing Pub Date : 2011-12-22 DOI: 10.1109/ICIIP.2011.6108937

M. Abdullah

引用次数: 1