We propose a two-dimensional (2D) image generation algorithm to inverse design the terahertz metasurfaces based on graphical representation. This image generation algorithm can produce high-precision metasurface struc...
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In a traditional multi-view image generation algorithm, partial image information might be lost at the pixel mapping step during the 3D image acquisition. A lower hardware cost and shorter operation time can be realiz...
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In a traditional multi-view image generation algorithm, partial image information might be lost at the pixel mapping step during the 3D image acquisition. A lower hardware cost and shorter operation time can be realized if an effective algorithm is employed. Therefore, a fast multi-view image rendering method based on reverse search is proposed in this paper, it uses pixel mapping information to derive a rendering image. Compared with the conventional depth-image-based rendering (DIBR) which using multiple images, the method only generates one image with reverse mapping in the image rendering step. First, the parallax range of the original image is calculated. Then, a warping image is generated through reverse mapping;this image has contained information for eight different viewpoints. Finally, the image modification can be made. Experimental results show that the proposed method effectively reduces rendering time and memory size by 58.82% and 83.78%, respectively. In addition, the mean structural similarity between the two images created by DIBR and our method is 1, which means that our method has the same effect as DIBR.
Synthetic pattern generation procedures have various applications, and a number of approaches (fractals, L-systems, etc.) have been devised. A fundamental underlying question is: will new pattern generationalgorithms...
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Synthetic pattern generation procedures have various applications, and a number of approaches (fractals, L-systems, etc.) have been devised. A fundamental underlying question is: will new pattern generationalgorithms continue to be invented, or is there some "universal'' algorithm that can generate all (and only) the perceptually distinguishable images, or even all members of a restricted class of patterns such as logos or letterforms? In fact there are many complete algorithms that can generate all possible images, but most images are random and not perceptually distinguishable. Counting arguments show that the percentage of distinguishable images that will be generated by such complete algorithms is vanishingly small. In this paper we observe that perceptually distinguishable images are compressible. Using this observation it is evident that algorithmic complexity provides an appropriate framework for discussing the question of a universal image generator. We propose a natural thesis for describing perceptually distinguishable images and argue its validity. Based on it, we show that there is no program that generates all (and only) these images. Although this is an abstract result, it may have importance for graphics and other fields that deal with compressible signals. In essence, new representations and pattern generationalgorithms will continue to be developed;there is no feasible "super algorithm'' that is capable of all things. (C) 2011 Elsevier Inc. All rights reserved.
Synthetic pattern generation procedures have various applications, and a number of approaches (fractals, L-systems, etc.) have been devised. A fundamental underlying question is: will new pattern generationalgorithms...
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Synthetic pattern generation procedures have various applications, and a number of approaches (fractals, L-systems, etc.) have been devised. A fundamental underlying question is: will new pattern generationalgorithms continue to be invented, or is there some "universal'' algorithm that can generate all (and only) the perceptually distinguishable images, or even all members of a restricted class of patterns such as logos or letterforms? In fact there are many complete algorithms that can generate all possible images, but most images are random and not perceptually distinguishable. Counting arguments show that the percentage of distinguishable images that will be generated by such complete algorithms is vanishingly small. In this paper we observe that perceptually distinguishable images are compressible. Using this observation it is evident that algorithmic complexity provides an appropriate framework for discussing the question of a universal image generator. We propose a natural thesis for describing perceptually distinguishable images and argue its validity. Based on it, we show that there is no program that generates all (and only) these images. Although this is an abstract result, it may have importance for graphics and other fields that deal with compressible signals. In essence, new representations and pattern generationalgorithms will continue to be developed;there is no feasible "super algorithm'' that is capable of all things. (C) 2011 Elsevier Inc. All rights reserved.
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