The theoretical framework of visual simulation in virtual reality is discussed. The new concept of visual image space is supposed. On the basis of visual image space, in visual perceptive sense, VR is considered as a ...The theoretical framework of visual simulation in virtual reality is discussed. The new concept of visual image space is supposed. On the basis of visual image space, in visual perceptive sense, VR is considered as a spatial simulation. The objective of the spatial simulation is to transform physical space to visual image space. Last, the prototype system, surveying & mapping virtual Reality (SMVR), is developed, and the space simulation above is realized. By use of SMVR, the real 3D representation, 3D visual analysis, virtual plan and designs can be implemented.展开更多
Ray-space based arbitrary viewpoint rendering without complex object segmentation or model construction is the main technology to realize Free Viewpoint Video(FVV) system for complex scenes. Ray-space interpolation an...Ray-space based arbitrary viewpoint rendering without complex object segmentation or model construction is the main technology to realize Free Viewpoint Video(FVV) system for complex scenes. Ray-space interpolation and compression are two key techniques for the solution. In this paper,correlation among multiple epipolar lines in ray-space data is analyzed,and a new method of ray-space interpolation with multi-epipolar lines matching is proposed. Comparing with the pixel-based matching interpolation method and the block-based matching interpolation method,the proposed method can achieve higher Peak Signal to Noise Ratio(PSNR) in interpolating rayspace data and rendering arbitrary viewpoint images.展开更多
Computational imaging describes the whole imaging process from the perspective of light transport and information transmission, features traditional optical computing capabilities, and assists in breaking through the ...Computational imaging describes the whole imaging process from the perspective of light transport and information transmission, features traditional optical computing capabilities, and assists in breaking through the limitations of visual information recording. Progress in computational imaging promotes the development of diverse basic and applied disciplines. In this review, we provide an overview of the fundamental principles and methods in computational imaging, the history of this field, and the important roles that it plays in the development of science. We review the most recent and promising advances in computational imaging, from the perspective of different dimensions of visual signals, including spatial dimension, temporal dimension, angular dimension, spectral dimension, and phase. We also discuss some topics worth studying for future developments in computational imaging.展开更多
Remote sensing based land cover mapping at large scale is time consuming when using either supervised or unsupervised clas- sification approaches. This article used a fast clustering method---Clustering by Eigen Space...Remote sensing based land cover mapping at large scale is time consuming when using either supervised or unsupervised clas- sification approaches. This article used a fast clustering method---Clustering by Eigen Space Transformation （CBEST） to pro- duce a land cover map for China. Firstly, 508 Landsat TM scenes were collected and processed. Then, TM images were clus- tered by combining CBEST and K-means in each pre-defined ecological zone （50 in total for China）. Finally, the obtained clusters were visually interpreted as land cover types to complete a land cover map. Accuracy evaluation using 2159 test sam- pies indicates an overall accuracy of 71.7% and a Kappa coefficient of 0.64. Comparisons with two global land cover products （i.e., Finer Resolution Observation and Monitoring of Global Land Cover （FROM-GLC） and GlobCover 2009） also indicate that our land cover result using CBEST is superior in both land cover area estimation and visual effect for different land cover types.展开更多
文摘The theoretical framework of visual simulation in virtual reality is discussed. The new concept of visual image space is supposed. On the basis of visual image space, in visual perceptive sense, VR is considered as a spatial simulation. The objective of the spatial simulation is to transform physical space to visual image space. Last, the prototype system, surveying & mapping virtual Reality (SMVR), is developed, and the space simulation above is realized. By use of SMVR, the real 3D representation, 3D visual analysis, virtual plan and designs can be implemented.
基金the National Natural Science Foundation of China (No.60472100)the Natural Science Foundation of Zhejiang Province (No.Y105577)the Key Project of Chinese Ministry of Education (No.206059).
文摘Ray-space based arbitrary viewpoint rendering without complex object segmentation or model construction is the main technology to realize Free Viewpoint Video(FVV) system for complex scenes. Ray-space interpolation and compression are two key techniques for the solution. In this paper,correlation among multiple epipolar lines in ray-space data is analyzed,and a new method of ray-space interpolation with multi-epipolar lines matching is proposed. Comparing with the pixel-based matching interpolation method and the block-based matching interpolation method,the proposed method can achieve higher Peak Signal to Noise Ratio(PSNR) in interpolating rayspace data and rendering arbitrary viewpoint images.
基金Project supported by the National Natural Science Foundation of China （Nos. 61327902 and 61631009）
文摘Computational imaging describes the whole imaging process from the perspective of light transport and information transmission, features traditional optical computing capabilities, and assists in breaking through the limitations of visual information recording. Progress in computational imaging promotes the development of diverse basic and applied disciplines. In this review, we provide an overview of the fundamental principles and methods in computational imaging, the history of this field, and the important roles that it plays in the development of science. We review the most recent and promising advances in computational imaging, from the perspective of different dimensions of visual signals, including spatial dimension, temporal dimension, angular dimension, spectral dimension, and phase. We also discuss some topics worth studying for future developments in computational imaging.
基金partially supported by the National High-tech R&D Program of China(Grant No.2009AA12200101)a research grant from Tsinghua University(Grant No.2012Z02287)
文摘Remote sensing based land cover mapping at large scale is time consuming when using either supervised or unsupervised clas- sification approaches. This article used a fast clustering method---Clustering by Eigen Space Transformation （CBEST） to pro- duce a land cover map for China. Firstly, 508 Landsat TM scenes were collected and processed. Then, TM images were clus- tered by combining CBEST and K-means in each pre-defined ecological zone （50 in total for China）. Finally, the obtained clusters were visually interpreted as land cover types to complete a land cover map. Accuracy evaluation using 2159 test sam- pies indicates an overall accuracy of 71.7% and a Kappa coefficient of 0.64. Comparisons with two global land cover products （i.e., Finer Resolution Observation and Monitoring of Global Land Cover （FROM-GLC） and GlobCover 2009） also indicate that our land cover result using CBEST is superior in both land cover area estimation and visual effect for different land cover types.
