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Retinally reconstructed images: digital images having a resolution match with the human eye

机译:视网膜重建图像:分辨率与人眼匹配的数字图像

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Current digital image/video storage, transmission and display technologies use uniformly sampled images. On the other hand, the human retina has a nonuniform sampling density that decreases dramatically as the solid angle from the visual fixation axis increases. Therefore, there is sampling mismatch. This paper introduces retinally reconstructed images (RRI), a representation of digital images that enables a resolution match with the retina. To create an RRI, the size of the input image, the viewing distance and the fixation point should be known. In the coding phase, we compute the "retinal codes", which consist of the retinal sampling locations onto which the image projects, together with the retinal outputs at these locations. In the decoding phase, we use the backprojection of the retinal codes onto the input image grid as B-spline control coefficients, in order to construct a 3D B-spline surface with nonuniform resolution properties. An RRI is then created by mapping the B-spline surface onto a uniform grid, using triangulation. Transmitting or storing the "retinal codes" instead of the full resolution images enables up to two orders of magnitude data compression, depending on the resolution of the input image, the size of the input image and the viewing distance. The data reduction capability of retinal codes and RRI is promising for digital video storage and transmission applications. However, the computational burden can be substantial in the decoding phase.
机译:当前的数字图像/视频存储,传输和显示技术使用统一采样的图像。另一方面,人类视网膜具有不均匀的采样密度,该采样密度随着与视觉固定轴的立体角的增加而急剧降低。因此,存在采样不匹配。本文介绍了视网膜重建图像(RRI),它是数字图像的一种表示形式,能够实现与视网膜的分辨率匹配。要创建RRI,应知道输入图像的大小,观看距离和注视点。在编码阶段,我们计算“视网膜码”,该“视网膜码”由图像投影到的视网膜采样位置以及这些位置处的视网膜输出组成。在解码阶段,我们将视网膜代码的反投影作为B样条控制系数使用到输入图像网格上,以构造分辨率特性不一致的3D B样条表面。然后,通过三角测量将B样条曲面映射到均匀网格上,从而创建RRI。传输或存储“视网膜码”而不是全分辨率图像,取决于输入图像的分辨率,输入图像的大小和观看距离,最多可以实现两个数量级的数据压缩。视网膜代码和RRI的数据缩减功能在数字视频存储和传输应用中很有希望。但是,在解码阶段,计算负担可能很大。

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