不产生精度截断及数据膨胀的图像金字塔

图像金字塔是处理和分析数字图像的重要工具。以图像金字塔为研究对象，旨在减小图像金字塔的存储量，同时解决恢复数据时的精度截断问题。从同一思想出发，提出了两种新的金字塔结构：类均值金字塔与类高斯金字塔；它们都是通过对子像素的简单运算来求得父像素，而这种运算不存在精度截断问题，也不需要额外的比特来保存小数。由于从父像素能够反推出它的子像素之一，所以，在存储金字塔时可以舍弃这部分子像素，从而使所需存储的像素数仅与原始图像相同。对精度、存储量以及构建速度的理论分析与实验结果表明，该金字塔结构具有优良的总体性能。

Image Pyramid Structures without Truncation and Data Expansion

Image pyramid is an important tool for processing and analyzing digital images. This study focuses on image pyramid, and finds out an approach to reduce the data volume of them and solve the problem of truncation in precision. Based on a same idea, we propose two kinds of image pyramid: the mean-like pyramid and the Gaussian-like pyramid. In them, father-pixels can be got by simple calculations of their son-pixels; there is no problem of truncation in such calculations, and no extra bits are needed to store decimals. Besides, as some son-pixels can be recovered from their father-pixels, they can be dropped when storing a pyramid. Thereby, the number of pixels need to be stored is equal to that of the original image only. Its shown that the proposed pyramid structures have good performance in general by theoretic analysis and experimental on precision, data volume and speed of creation.