Acceleration of Histogram-Based Contrast Enhancement via Selective Downsampling

In this paper, we propose a general framework to accelerate the universal histogram-based image contrast enhancement (CE) algorithms. Both spatial and gray-level selective down- sampling of digital images are adopted to decrease computational cost, while the visual quality of enhanced images is still preserved and without apparent degradation. Mapping function calibration is novelly proposed to reconstruct the pixel mapping on the gray levels missed by downsampling. As two case studies, accelerations of histogram equalization (HE) and the state-of-the-art global CE algorithm, i.e., spatial mutual information and PageRank (SMIRANK), are presented detailedly. Both quantitative and qualitative assessment results have verified the effectiveness of our proposed CE acceleration framework. In typical tests, computational efficiencies of HE and SMIRANK have been speeded up by about 3.9 and 13.5 times, respectively.Comment: accepted by IET Image Processin

Contrast Enhancement of Brightness-Distorted Images by Improved Adaptive Gamma Correction

As an efficient image contrast enhancement (CE) tool, adaptive gamma correction (AGC) was previously proposed by relating gamma parameter with cumulative distribution function (CDF) of the pixel gray levels within an image. ACG deals well with most dimmed images, but fails for globally bright images and the dimmed images with local bright regions. Such two categories of brightness-distorted images are universal in real scenarios, such as improper exposure and white object regions. In order to attenuate such deficiencies, here we propose an improved AGC algorithm. The novel strategy of negative images is used to realize CE of the bright images, and the gamma correction modulated by truncated CDF is employed to enhance the dimmed ones. As such, local over-enhancement and structure distortion can be alleviated. Both qualitative and quantitative experimental results show that our proposed method yields consistently good CE results

The NAH based on complex cepstrum method in a closed space

NAH method in non-free sound field reconstruction of the sound source will lead to considerable error. This paper proposes a method to reconstruct the sound source in a closed space. In the closed space, the total sound pressure is the sum of the source radiation pressure and the reflected sound pressure from medium interface. Reflections from medium interface is a convolution noise, rather than additive noise. In order to reconstruct a sound source in the closed space, in this paper we first adopt the complex cepstrum method to separate and radiation pressure and the reflected sound pressure, then filter them to reduction of reflected sound pressure, and then reconstruct the sound source. The simulation results show the correctness and effectiveness of the method

A Review of Smart Materials in Tactile Actuators for Information Delivery

As the largest organ in the human body, the skin provides the important sensory channel for humans to receive external stimulations based on touch. By the information perceived through touch, people can feel and guess the properties of objects, like weight, temperature, textures, and motion, etc. In fact, those properties are nerve stimuli to our brain received by different kinds of receptors in the skin. Mechanical, electrical, and thermal stimuli can stimulate these receptors and cause different information to be conveyed through the nerves. Technologies for actuators to provide mechanical, electrical or thermal stimuli have been developed. These include static or vibrational actuation, electrostatic stimulation, focused ultrasound, and more. Smart materials, such as piezoelectric materials, carbon nanotubes, and shape memory alloys, play important roles in providing actuation for tactile sensation. This paper aims to review the background biological knowledge of human tactile sensing, to give an understanding of how we sense and interact with the world through the sense of touch, as well as the conventional and state-of-the-art technologies of tactile actuators for tactile feedback delivery

Nanoscale lithography mediated by surface self-assembly of 16-[3,5-bis(mercaptomethyl)phenoxy]hexadecanoic acid on Au(111) investigated by scanning probe microscopy

The solution-phase self-assembly of bidentate 16-[3,5-bis(mercaptomethyl) phenoxy]hexadecanoic acid (BMPHA) on Au(111) was studied using nano-fabrication protocols with scanning probe nanolithography and immersion particle lithography. Molecularly thin films of BMPHA prepared by surface self-assembly have potential application as spatially selective layers in sensor designs. Either monolayer or bilayer films of BMPHA can be formed under ambient conditions, depending on the parameters of concentration and immersion intervals. Experiments with scanning probe-based lithography (nanoshaving and nanografting) were applied to measure the thickness of BMPHA films. The thickness of a monolayer and bilayer film of BMPHA on Au(111) were measured in situ with atomic force microscopy using n-octadecanethiol as an internal reference. Scanning probe-based nanofabrication provides a way to insert nanopatterns of a reference molecule of known dimensions within a matrix film of unknown thickness to enable a direct comparison of heights and surface morphology. Immersion particle lithography was used to prepare a periodic arrangement of nanoholes within films of BMPHA. The nanoholes could be backfilled by immersion in a SAM solution to produce nanodots of n-octadecanethiol surrounded by a film of BMPHA. Test platforms prepared by immersion particle lithography enables control of the dimensions of surface sites to construct supramolecular assemblies

Multistage Sampling and Optimization for Forest Volume Inventory Based on Spatial Autocorrelation Analysis

It is important to achieve estimates at the minimum cost, with no greater uncertainty than that which is appropriate for the objectives of the inventory. The aim of this study was to estimate the forest volume efficiently and accurately by sampling and analyzing the existing forest survey data, which is also a technical challenge. In this work, we used the spatial statistics tools in the ArcGIS software to analyze spatial autocorrelations with the data from the sixth to ninth continuous forest inventories (CFI) of Sichuan Province from 2002, 2007, 2012, and 2017. Based on the sampling framework of the CFI, we divided the sampling units into five groups using different methods to create the second-stage samples. Combined with the spatial autocorrelation analysis results, we selected certain samples from the collection of second-stage samples through stratified sampling to form the third-stage sampling units. We applied the sampling ratio, sampling accuracy, workload, and costs as the evaluation indexes for the sampling efficiency analysis. The main results are as follows: Before conversion, the forest volume density had a positively skewed distribution. There was substantial positive spatial autocorrelation, and its intensity was affected by the distance scale, especially at 187.3 km, where the spatial processes of clustering were most pronounced. At the significance level of α = 0.01, the high-volume stands were mainly concentrated in the Aba Prefecture, Garze Prefecture, and Liangshan Prefecture, while the low-volume stands were mainly concentrated in the Sichuan Basin region. The heterogeneous gatherings were staggered between the high-volume areas and low-volume areas, while the transition zone between the three prefecture regions and basin region was randomly distributed. With 95% reliability, the average estimation accuracy of the systematic sampling, random sampling, and cluster sampling in the second stage was 94.09%, which is less accurate than the CFI estimation accuracy. The mean correlation coefficients (R) between the estimated value of the forest volume and the observations of the systematic sampling, random sampling, and cluster sampling in the second stage were 0.95, 0.98, and 0.96, respectively. The relative differences (RD%) were −0.52, −0.39, and −0.36, respectively. The spatial stratified sampling in the third stage, which is based on spatial distribution pattern information, significantly reduced the sampling ratio to 1.68 per 10,000, compared with the average ratios of the CFI sampling and second-stage sampling, which were 13.73 per 10,000 and 2.75 per 10,000, respectively. With 95% reliability, the mean accuracy of the spatial stratified sampling in the third stage was 93.05%, the R was 0.94, and the RD% was −0.09. Spatial stratified sampling is more in line with the actual work conducted in annual surveys because it effectively reduces the sample size using prior spatial information, which can better meet the requirements of the annual output

A new method to estimate branch biomass from terrestrial laser scanning data by bridging tree structure models

Background and Aims Branch biomass and other attributes are important for estimating the carbon budget of forest stands and characterizing crown structure. As destructive measuring is time-consuming and labour-intensive, terrestrial laser scanning (TLS) as a solution has been used to estimate branch biomass quickly and non-destructively. However, branch information extraction from TLS data alone is challenging due to occlusion and other defects, especially for estimating individual branch attributes in coniferous trees. Methods This study presents a method, entitled TSMtls, to estimate individual branch biomass non-destructively and accurately by combining tree structure models and TLS data. The TSMtls method constructs the stem-taper curve from TLS data, then uses tree structure models to determine the number, basal area and biomass of individual branches at whorl level. We estimated the tree structural model parameters from 122 destructively measured Scots pine (Pinus sylvestris) trees and tested the method on six Scots pine trees that were first TLS-scanned and later destructively measured. Additionally, we estimated the branch biomass using other TLS-based approaches for comparison. Key Results Tree-level branch biomass estimates derived from TSMtls showed the best agreement with the destructive measurements [coefficient of variation of root mean square error (CV-RMSE) = 9.66 % and concordance correlation coefficient (CCC) = 0.99], outperforming the other TLS-based approaches (CV-RMSE 12.97-57.45 % and CCC 0.43-0.98 ). Whorl-level individual branch attributes estimates produced from TSMtls showed more accurate results than those produced from TLS data directly. Conclusions The results showed that the TSMtls method proposed in this study holds promise for extension to more species and larger areas.Peer reviewe

Reduced Dynamic Interactions Within Intrinsic Functional Brain Networks in Early Blind Patients

Neuroimaging studies in early blind (EB) patients have shown altered connections or brain networks. However, it remains unclear how the causal relationships are disrupted within intrinsic brain networks. In our study, we used spectral dynamic causal modeling (DCM) to estimate the causal interactions using resting-state data in a group of 20 EB patients and 20 healthy controls (HC). Coupling parameters in specific regions were estimated, including the medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), and inferior parietal lobule (IPC) in the default mode network (DMN); dorsal anterior cingulate cortex (dACC) and bilateral anterior insulae (AI) in the salience network (SN), and bilateral frontal eye fields (FEF) and superior parietal lobes (SPL) within the dorsal attention network (DAN). Statistical analyses found that all endogenous connections and the connections from the mPFC to bilateral IPCs in EB patients were significantly reduced within the DMN, and the effective connectivity from the PCC and lIPC to the mPFC, and from the mPFC to the PCC were enhanced. For the SN, all significant connections in EB patients were significantly decreased, except the intrinsic right AI connections. Within the DAN, more significant effective connections were observed to be reduced between the EB and HC groups, while only the connections from the right SPL to the left SPL and the intrinsic connection in the left SPL were significantly enhanced. Furthermore, discovery of more decreased effective connections in the EB subjects suggested that the disrupted causal interactions between specific regions are responsive to the compensatory brain plasticity in early deprivation

Potential distributions of seven sympatric sclerophyllous oak species in Southwest China depend on climatic, non-climatic, and independent spatial drivers

Key message An ensemble modelling approach was performed to predict the distributions of seven sympatric sclerophyllous oak species in the Hengduan Mountains of Southwest China. Spatial eigenvector filters revealed missing factors in addition to commonly used environmental variables, thus effectively improved predictive accuracy for the montane oak species. This study identified a richness center of sclerophyllous oaks, which provides a reference for proper conservation and utilization of oak resources. Context As key species and important trees for construction- and fuel-wood, montane sclerophyllous oaks (Quercus sect. Heterobalanus) in the Hengduan Mountains of Southwest China are threatened by climate change, habitat fragmentation, and human activities. Aims This study aims to simulate the potential distributions of seven sympatric sclerophyllous oak species with an emphasis on exploring the relative importance of climatic, non-climatic, and additional spatial factors. Methods We performed an ensemble modelling approach of six ecological niche models in combination with spatial eigenvector filters to predict the potential distributions of seven oak species. Results The results elucidated that temperature seasonality, followed by land use/cover and the human influence index were the most critical variables controlling oak species distributions. Regardless of the selected algorithm, the best performing models for most oaks combined climatic and non-climatic factors as well as additional spatial filters. Conclusion It is necessary to strengthen the conservation of oak species at the junction of Sichuan and Yunnan Province where we found the richness center of the studied oaks. Our research provides essential insights for the rational conservation and management of sclerophyllous oak species, suggesting that spatial constraints might reflect limited ability of migration under future climate change.Peer reviewe