从连续表示中重新审视非局部自相似性
IEEE transactions on pattern analysis and machine intelligence
|September 19, 2024
概括
本研究介绍了基于连续表示的非局部 (CRNL) 方法,增强在网格和网格之外的数据的非局部自相似性 (NSS). 在各种数据处理任务中,CRNL提供了更高的有效性和效率.
科学领域:
- 计算机视觉 计算机视觉
- 数据科学数据科学数据科学
- 信号处理 信号处理
背景情况:
- 非局部自我相似性 (NSS) 是多维数据处理的强大先验,主要应用于像图像和视频这样的网格数据.
- 现有的NSS方法仅限于网格数据,无法处理新出现的网格外数据,例如点云和天气数据.
研究的目的:
- 开发一种新的方法,将NSS的适用性扩展到网络上和网络之外的数据.
- 引入基于连续表示的非局部 (CRNL) 方法,统一不同数据类型的自我相似度.
- 提高基于NSS的数据处理的效率和有效性.
主要方法:
- 从连续表示的角度重新审视NSS.
- 提出CRNL方法与统一的自我相似度测量在网格上和网格之外的数据.
- 采用合低级函数因子化,对非局部连续组进行紧和高效的表示,捕捉组间的相似性.
主要成果:
- 通过成功处理网上 (图像绘制,无雾化) 和网外 (天气数据预测,点云恢复) 数据,CRNL展示了多功能性.
- 该方法在有效性和效率方面,与传统的NSS方法相比,实现了更高的性能.
- 结合的低等级因子化有效地利用非本地群体内部和跨区域的相似性,优于忽视跨群体相似性的方法.
结论:
- 该CRNL方法有效地将NSS原则扩展到更广泛的数据范围,包括离网格格式.
- CRNL为非本地数据处理提供了一种统一而高效的方法,其性能优于现有的最先进的方法.
- 连续代表视角和相应的低等级因子化是使CRNL的广泛适用性和增强性能成为可能的关键创新.
相关概念视频
Modeling and Similitude
249
Scaled modeling is a fundamental technique in engineering, enabling the study of large and complex systems by creating smaller, manageable replicas that recreate critical characteristics of the original. In hydrology and civil infrastructure, for example, scaled models of dams help analyze water flow, turbulence, and pressure. This method allows for accurate predictions of real-world behavior within a controlled environment, significantly reducing the cost and time involved in full-scale...
249
Residuals and Least-Squares Property
7.3K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.3K
Woodward–Hoffmann Selection Rules and Microscopic Reversibility
3.0K
Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
3.0K
Perceptual Constancy
364
Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
364
The Representativeness Heuristic
15.8K
The representative heuristic describes a biased way of thinking, in which you unintentionally stereotype someone or something. For example, you may assume that your professors spend their free time reading books and engaging in intellectual conversation, because the idea of them spending their time playing volleyball or visiting an amusement park does not fit in with your stereotypes of professors.
15.8K
State Space Representation
171
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Consider an RLC circuit, a...
171


