The amplitude of Fourier spectra for natural scenes falls with spatial frequency (f) and is described by the equation, 1/f, where exponent α corresponds to the slope of the spectral drop-off. For natural scenes α takes on intermediate values ~1.25, reflecting their scale invariance. It is also well-established that, on average, images with natural scene statistics are preferred to those that deviate from these properties. Although this average pattern of preference for images with the intermediate values of α is robust, there are also marked individual differences in preference for different levels of α. This study investigated the effects of adaptation on average and individual visual preferences for synthetic filtered noise images varying in α. Participant preferences (N = 58) were measured via a 2AFC task prior to adaptation (baseline) and post-adaptation There were 3 adaptation conditions (α = 0.25, 1.25, 2.25) and 5 test levels of α (0.25, 0.75, 1.25, 1.75, 2.25). On average, the adaptation elevated preferences for test images with α matching the adaptor conditions, especially in adaptor conditions, α = 0.25 and 2.25. We also observed marked individual differences in preference for different levels of α. These different preference profiles remained stable throughout the experiment and affected the levels of adaptation observed in different adaptation conditions.
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http://dx.doi.org/10.1016/j.visres.2020.11.011 | DOI Listing |
Sensors (Basel)
January 2025
College of Electronics and Information Engineering, South-Central Minzu University, Wuhan 430074, China.
Drones are extensively utilized in both military and social development processes. Eliminating the reliance of drone positioning systems on GNSS and enhancing the accuracy of the positioning systems is of significant research value. This paper presents a novel approach that employs a real-scene 3D model and image point cloud reconstruction technology for the autonomous positioning of drones and attains high positioning accuracy.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Geosciences, Yangtze University, Wuhan 430100, China.
Roadside tree segmentation and parameter extraction play an essential role in completing the virtual simulation of road scenes. Point cloud data of roadside trees collected by LiDAR provide important data support for achieving assisted autonomous driving. Due to the interference from trees and other ground objects in street scenes caused by mobile laser scanning, there may be a small number of missing points in the roadside tree point cloud, which makes it familiar for under-segmentation and over-segmentation phenomena to occur in the roadside tree segmentation process.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Computer Science, Xi'an Polytechnic University, Xi'an 710600, China.
Interacting hand reconstruction presents significant opportunities in various applications. However, it currently faces challenges such as the difficulty in distinguishing the features of both hands, misalignment of hand meshes with input images, and modeling the complex spatial relationships between interacting hands. In this paper, we propose a multilevel feature fusion interactive network for hand reconstruction (HandFI).
View Article and Find Full Text PDFSensors (Basel)
December 2024
Laboratory of Target Microwave Properties, Deqing Academy of Satellite Applications, Deqing 313200, China.
Using microwave remote sensing to invert forest parameters requires clear canopy scattering characteristics, which can be intuitively investigated through scattering measurements. However, there are very few ground-based measurements on forest branches, needles, and canopies. In this study, a quantitative analysis of the canopy branches, needles, and ground contribution of Masson pine scenes in C-, X-, and Ku-bands was conducted based on a microwave anechoic chamber measurement platform.
View Article and Find Full Text PDFPLoS One
January 2025
Dept. of Medical Physics and Acoustics, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany.
Music pre-processing methods are currently becoming a recognized area of research with the goal of making music more accessible to listeners with a hearing impairment. Our previous study showed that hearing-impaired listeners preferred spectrally manipulated multi-track mixes. Nevertheless, the acoustical basis of mixing for hearing-impaired listeners remains poorly understood.
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