Mathematical Properties of Pyramid-Transform-Based Resolution Conversion and Its Applications

IF 1.3 4区 数学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Kento Hosoya, Kouki Nozawa, Hayato Itoh, Atsushi Imiya
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Abstract

In this paper, we aim to clarify the statistical and geometric properties of linear resolution conversion for registration between different resolutions observed using the same modality. The pyramid transform is achieved by smoothing and downsampling. The dual operation of the pyramid transform is achieved by linear smoothing after upsampling. The rational-order pyramid transform is decomposed into upsampling for smoothing and the conventional integer-order pyramid transform. By controlling the ratio between upsampling for smoothing and downsampling in the pyramid transform, the rational-order pyramid transform is computed. The tensor expression of the multiway pyramid transform implies that the transform yields orthogonal base systems for any ratio of the rational pyramid transform. The numerical evaluation of the transform shows that the rational-order pyramid transform preserves the normalised distribution of greyscale in images.

Abstract Image

基于金字塔变换的分辨率转换的数学特性及其应用
本文旨在阐明线性分辨率转换的统计和几何特性,以便在使用同一模式观测到的不同分辨率之间进行配准。金字塔变换是通过平滑和下采样实现的。金字塔变换的双重操作是通过上采样后的线性平滑来实现的。有理阶金字塔变换分解为用于平滑的上采样和传统的整数阶金字塔变换。通过控制金字塔变换中平滑上采样和下采样的比例,可以计算出有理阶金字塔变换。多向金字塔变换的张量表达式意味着,对于有理阶金字塔变换的任何比率,该变换都能产生正交的基础系统。对变换的数值评估表明,有理阶金字塔变换保留了图像中灰度的归一化分布。
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来源期刊
Journal of Mathematical Imaging and Vision
Journal of Mathematical Imaging and Vision 工程技术-计算机:人工智能
CiteScore
4.30
自引率
5.00%
发文量
70
审稿时长
3.3 months
期刊介绍: The Journal of Mathematical Imaging and Vision is a technical journal publishing important new developments in mathematical imaging. The journal publishes research articles, invited papers, and expository articles. Current developments in new image processing hardware, the advent of multisensor data fusion, and rapid advances in vision research have led to an explosive growth in the interdisciplinary field of imaging science. This growth has resulted in the development of highly sophisticated mathematical models and theories. The journal emphasizes the role of mathematics as a rigorous basis for imaging science. This provides a sound alternative to present journals in this area. Contributions are judged on the basis of mathematical content. Articles may be physically speculative but need to be mathematically sound. Emphasis is placed on innovative or established mathematical techniques applied to vision and imaging problems in a novel way, as well as new developments and problems in mathematics arising from these applications. The scope of the journal includes: computational models of vision; imaging algebra and mathematical morphology mathematical methods in reconstruction, compactification, and coding filter theory probabilistic, statistical, geometric, topological, and fractal techniques and models in imaging science inverse optics wave theory. Specific application areas of interest include, but are not limited to: all aspects of image formation and representation medical, biological, industrial, geophysical, astronomical and military imaging image analysis and image understanding parallel and distributed computing computer vision architecture design.
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