自然图像的稀疏编码
Sparse Coding on Natural Image
稀疏编码模型中最重要的部分是如何获取用于编码图像的基函数字典。本文首先使用基于学习的方法，在高斯白化之后的训练图集上得到了超完备基函数集合的子集。该函数集合具有人眼视觉系统所具备的局部性和带通特性，其响应概率分布也满足稀疏分布，可以作为用于编码图像的基函数。
he most important part of sparse coding model is to create the over complete base functions dictionary by which the image is coded. In the beginning, learning based method is used in this paper. And a sub set of over complete base dictionary is obtained among training images which have been Gaussian whiten. The base functions we got have the character of localization and band pass which is the same as human visual system. Due to its response of sparsely distribution, the set could be used to code images as bases.
赵德斌、伊里奇
计算技术、计算机技术
图像压缩稀疏编码人视觉系统
Image Compressionsparse codinghuman visual system
赵德斌,伊里奇.自然图像的稀疏编码[EB/OL].(2010-01-27)[2025-08-18].http://www.paper.edu.cn/releasepaper/content/201001-1146.点此复制
评论