VRHD: An Interactive Visualization Method for Hyperspectral Data Based on Volume Rendering
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As the development of data visualization technology, it becomes more and more convenient to commit data analyzing and mining in some research areas. Data visualization paves the way to understand the abstract numbers in an intuitive manner. This paper focuses on the hyperspectral data analysis by visualization. We research the ray casting based volume data rendering method and propose the method termed Volume Rendering of Hyperspectral Data(VRHD) to visualize the hyperspectral data. The triple control elements including color, transparency and visual district are proposed to do the data analysis and solve the overlapping problem in cubic data visualization by traditional screen. The results prove that the proposed algorithm can help the data user or analyzer to grasp the character of the data such as noise distribution in an integral view.Keywords:
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To show the cerebrovascular volume date segmented from medical images,a new integration of multi-factor volume rendering algorithm was proposed.Firstly,the cerebral vascular volume data was classified into vascular and background voxels.Secondly,in the base of Ray-Casting,a new integration of multi-fusion volume rendering algorithm was proposed,considering cerebrovascular edge features,the distance between the viewpoint and the object,and the distance of the light source and the object.Finally,volume rendering was accelerated by using CUDA.The experimental results show that the cerebral vascular volume data can be displayed clearly,which is more coincident with the human vision,and real-time interaction.
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Ray casting algorithm is one important method to render CT volumes with 2D CT slices, and it can be accelerated using graphics hardware. In this paper, we developed an efficient volume rendering system based on ray casting using C++ and VTK, and designed common shading and classification transfer functions to highlight different organs/tissues of a CT volume. With this system we experimented CT volumes using CPU ray casting and GPU ray casting respectively, and then we did the same experiments on different graphics cards. The results showed that we can highlight the organs/tissues in which we are interested by setting proper transfer functions and that the rendering efficiency can be accelerated greatly using graphics cards with nVidia GPU GT220 or higher almost with the same visualization quality as that of CPU ray casting.
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Ray casting Algorithm is one of the basic algorithms used in the volume rendering of three dimensional data, which has a good operating and a simple description, but there are some obvious problems on the rendering speed and the precision. In this paper, a new intelligent volume rendering method, integrated the particle swarm optimization on transfer function design with the Ray-leaping rendering algorithm, is described, which make up the lack of rendering speed and precision in traditional ray casting algorithm. Then, the MITK is used to render a skull CT image sequence.
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This paper discusses the principle and implementation method of Ray-casting volume rendering algorithm. In order to enhance the image quality and speed of alternate operation, we improve the grads formula in Ray-casting volume rendering algorithm and compound method of the sampling points.
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Volume visualization is one of the advanced technologies in the field of medical image 3D visualization, the efficiency of the volume rendering algorithm directly influences the results of volume visualization. In allusion to the ray-casting volume rendering algorithm, a fast look-up empty voxels algorithm is proposed based on AABB, which shortens the length of ray integral and accelerates the volume rendering. The experiment results verify that the new algorithm is effective in raising rendering speed.
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Ray casting algorithm is achieved through using of the tools of VC++6.0 and OpenGL.Introduced the ray casting algorithm and the knowledge of OpenGL.The crucial experimental method is following.Firstly,the regular volume data needed in the process of volume rendering are obtained by the preprocess of original CT images,and the values of color and opacity are distributed to every data.Secondly,the image of head which the main part is the brain of person is rendered with the volume rendering,and the function of browse and rendering can be completed in three directions of space.However,the speed of rendering is slow.Experimental results show that a proper example of volume rendering is exemplified in the visualization of 3D the person's brain by ray casting algorithm,and the image of rendering is quite clear,the result of image is very satisfied.
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Ray-casting algorithm is usually used in medical volume visualization, but there are a lot of limitations inherent to this algorithm, like high computational demand, low quality images, or a fixed classification. In contrast, real-time high quality volume rendering algorithms are still a challenge nowadays. We introduce here an efficient and accurate volume rendering algorithm for medical images, and this algorithm can achieve up to 2.5 fps on PCs for 512×512×482×2 Byte volume. The algorithm classifies volume data into the foreground voxels and background voxels, and the former voxels are resampled using the similar LOD (Layer of Detail) technique, then optical attribute of the resampling points is determined by a new method. This method is reasonably associated with the distance between the object and the viewpoint, as well as the object and the light source. In addition, the background voxels are displayed by the accelerated method based on space leaping resampling. The results show that interactive volume rendering can be implemented for most medical volume data on PCs. Meanwhile, tissues or organs can be displayed clearly, which is more coincident with the human vision.
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In the medical image visualization, ray-casting algorithm is a common algorithm.However, traditional ray-casting algorithm is not efficient for real-time volume rendering because of the excessive calculation and the high redundancy .In this paper, the resampling process by skipping the empty voxel is improved according to the medical image characteristics existing concentrated empty voxel.Experimental results demonstrate that the improved algorithm can accelerate the rendering speed and maintenance the quality of rendering image simultaneously.
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Three dimensional visualization of medical volume data is achieved by many of the volume rendering algorithms either Direct or Indirect. The focus of our work is to make some simplifications in the Ray casting algorithm, a Direct Volume Rendering technique. The idea is to group the rays that are cast from similar voxels and the groups are verified for similarity on every successive sampling. This paper also compares the results with those results generated by the traditional ray casting in order ensure image quality. As the rays are cast in groups, the computational complexity of the rendering algorithm is reduced due to the decrease in the total number of samples being actually processed.
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Volume ray casting algorithm is widely recognized for high quality volume visualization. However, when rendering very large volume data sets, the original ray casting algorithm will lead to very inefficient random accesses in disk and make it very slowly to render the whole volume data set. In order to solve this problem, an efficient out-of-core volume ray casting method with a new out-of-core framework for processing large volume data sets based on consumer PC hardware is proposed in this paper. The new framework gives a transparent and efficient access to the volume data set cached in disk, while the new volume ray casting method minimizes the data exchange between hard disk and physical memory and performs comparatively fast high quality volume rendering. The experimental results indicate that the new method and framework are effective and efficient for the visualization of very large medical data sets.
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