In this paper,we propose a new directional multi-resolution ridgelet network(DMRN)based on the ridgelet frame theory,which uses the ridgelet as the activation function in a hidden layer.For the multi-resolution proper...In this paper,we propose a new directional multi-resolution ridgelet network(DMRN)based on the ridgelet frame theory,which uses the ridgelet as the activation function in a hidden layer.For the multi-resolution properties of the ridgelet function in the direction besides scale and position,DMRN has great capabilities in catching essential features of direction-rich data.It proves to be able to approximate any multivariate function in a more stable and efficient way,and optimal in approximating functions with spatial inhomogeneities.Besides,using binary ridgelet frame as the mathematical foundation in its construction,DMRN is more flexible with a simple structure.The construction and the learning algorithm of DMRN are given.Its approximation capacity and approximation rate are also analyzed in detail.Possibilities of applications to regression and recognition are included to demonstrate its superiority to other methods and feasibility in practice.Both theory analysis and simulation results prove its high efficiency.展开更多
This paper proposes a novel method for image magnification by exploiting the property that the intensity of an image varies along the direction of the gradient very quickly. It aims to maintain sharp edges and clear d...This paper proposes a novel method for image magnification by exploiting the property that the intensity of an image varies along the direction of the gradient very quickly. It aims to maintain sharp edges and clear details. The proposed method first calculates the gradient of the low-resolution image by fitting a surface with quadratic polynomial precision. Then,bicubic interpolation is used to obtain initial gradients of the high-resolution(HR) image. The initial gradients are readjusted to find the constrained gradients of the HR image, according to spatial correlations between gradients within a local window. To generate an HR image with high precision, a linear surface weighted by the projection length in the gradient direction is constructed. Each pixel in the HR image is determined by the linear surface. Experimental results demonstrate that our method visually improves the quality of the magnified image. It particularly avoids making jagged edges and bluring during magnification.展开更多
A switchable autostereoscopic 3-dimensional(3D) display device with wide color gamut is introduced in this paper. In conjunction with a novel directional quantum-dot(QD) backlight, the precise scanning control strateg...A switchable autostereoscopic 3-dimensional(3D) display device with wide color gamut is introduced in this paper. In conjunction with a novel directional quantum-dot(QD) backlight, the precise scanning control strategy, and the eye-tracking system, this spatial-sequential solution enables our autostereoscopic display to combine all the advantages of full resolution,wide color gamut, low crosstalk, and switchable 2D/3D. And also, we fabricated an autostereoscopic display prototype and demonstrated its performances effectively. The results indicate that our system can both break the limitation of viewing position and provide high-quality 3D images. We present two working modes in this system. In the spatial-sequential mode,the crosstalk is about 6%. In the time-multiplexed mode, the viewer should wear auxiliary and the crosstalk is about 1%,just next to that of a commercial 3D display(BENQ XL2707-B and View Sonic VX2268 WM). Additionally, our system is also completely compatible with active shutter glasses and its 3D resolution is same as its 2D resolution. Because of the excellent properties of the QD material, the color gamut can be widely extended to 77.98% according to the ITU-R recommendation BT.2020(Rec.2020).展开更多
基金supported by the National Natural Science Foundation of China (Grant No.60601029)the National Basic Research Program of China (No.A 50105020025).
文摘In this paper,we propose a new directional multi-resolution ridgelet network(DMRN)based on the ridgelet frame theory,which uses the ridgelet as the activation function in a hidden layer.For the multi-resolution properties of the ridgelet function in the direction besides scale and position,DMRN has great capabilities in catching essential features of direction-rich data.It proves to be able to approximate any multivariate function in a more stable and efficient way,and optimal in approximating functions with spatial inhomogeneities.Besides,using binary ridgelet frame as the mathematical foundation in its construction,DMRN is more flexible with a simple structure.The construction and the learning algorithm of DMRN are given.Its approximation capacity and approximation rate are also analyzed in detail.Possibilities of applications to regression and recognition are included to demonstrate its superiority to other methods and feasibility in practice.Both theory analysis and simulation results prove its high efficiency.
基金supported by the National Natural Science Foundation of China (Nos. 61332015, 61373078, 61572292, and 61272430)National Research Foundation for the Doctoral Program of Higher Education of China (No. 20110131130004)
文摘This paper proposes a novel method for image magnification by exploiting the property that the intensity of an image varies along the direction of the gradient very quickly. It aims to maintain sharp edges and clear details. The proposed method first calculates the gradient of the low-resolution image by fitting a surface with quadratic polynomial precision. Then,bicubic interpolation is used to obtain initial gradients of the high-resolution(HR) image. The initial gradients are readjusted to find the constrained gradients of the HR image, according to spatial correlations between gradients within a local window. To generate an HR image with high precision, a linear surface weighted by the projection length in the gradient direction is constructed. Each pixel in the HR image is determined by the linear surface. Experimental results demonstrate that our method visually improves the quality of the magnified image. It particularly avoids making jagged edges and bluring during magnification.
基金Project supported by the National Key R&D Program of China(Grant No.2016YFB0401503)the R&D Plan of Jiangsu Science and Technology Department,China(Grant No.BE2016173)
文摘A switchable autostereoscopic 3-dimensional(3D) display device with wide color gamut is introduced in this paper. In conjunction with a novel directional quantum-dot(QD) backlight, the precise scanning control strategy, and the eye-tracking system, this spatial-sequential solution enables our autostereoscopic display to combine all the advantages of full resolution,wide color gamut, low crosstalk, and switchable 2D/3D. And also, we fabricated an autostereoscopic display prototype and demonstrated its performances effectively. The results indicate that our system can both break the limitation of viewing position and provide high-quality 3D images. We present two working modes in this system. In the spatial-sequential mode,the crosstalk is about 6%. In the time-multiplexed mode, the viewer should wear auxiliary and the crosstalk is about 1%,just next to that of a commercial 3D display(BENQ XL2707-B and View Sonic VX2268 WM). Additionally, our system is also completely compatible with active shutter glasses and its 3D resolution is same as its 2D resolution. Because of the excellent properties of the QD material, the color gamut can be widely extended to 77.98% according to the ITU-R recommendation BT.2020(Rec.2020).
