10 research outputs found
A multi-focus image fusion method via region mosaicking on Laplacian pyramids
<div><p>In this paper, a method named Region Mosaicking on Laplacian Pyramids (RMLP) is proposed to fuse multi-focus images that is captured by microscope. First, the Sum-Modified-Laplacian is applied to measure the focus of multi-focus images. Then the density-based region growing algorithm is utilized to segment the focused region mask of each image. Finally, the mask is decomposed into a mask pyramid to supervise region mosaicking on a Laplacian pyramid. The region level pyramid keeps more original information than the pixel level. The experiment results show that RMLP has best performance in quantitative comparison with other methods. In addition, RMLP is insensitive to noise and can reduces the color distortion of the fused images on two datasets.</p></div
An illustration of density-connectivity with same mask label.
<p>An illustration of density-connectivity with same mask label.</p
Polyelectrolyte-Stabilized Graphene Oxide Liquid Crystals against Salt, pH, and Serum
Stabilization of colloids is of great
significance in nanoscience
for their fundamental research and practical applications. Electrostatic
repulsion-stabilized anisotropic colloids, such as graphene oxide
(GO), can form stable liquid crystals (LCs). However, the electrostatic
field would be screened by ions. To stabilize colloidal LCs against
electrolyte is an unsolved challenge. Here, an effective strategy
is proposed to stabilize GO LCs under harsh conditions by association
of polyelectrolytes onto GO sheets. Using sodium poly(styrene sulfonate)
(PSS) and poly[2-(methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl)ammonium
hydroxide (PMEDSAH), a kind of polyzwitterion, GO LCs were well-maintained
in the presence of NaCl (from 0 M to saturated), extreme pH (from
1 to 13), and serum. Moreover, PSS- or PMEDSAH-coated chemically reduced
GO (rGO) also showed stability against electrolyte
Flowchart of multi-focus images fusion based on RMLP approach.
<p>Flowchart of multi-focus images fusion based on RMLP approach.</p
Illustration of the S2 Dataset and its fusion results.
<p>(a)-(f) are six random sampled examples from sixty multi-focus images, (g) is the mask image with only EOF measurement, (h) is the mask image with the proposed DBRG segmentation algorithm. (i) is the fusion result of the Laplacian pyramid (LP) method and (j)is the fusion result of the proposed RMLP.</p
An illustration of 3D object imaging with an optical camera.
<p><i>I</i><sub><i>A</i></sub> and <i>I</i><sub><i>B</i></sub> are image pixels of point <i>A</i> and <i>B</i> respectively. With the current focal length, the surface that point <i>A</i> lies on is focused while that of point <i>B</i> is not. It can be seen1 that in-focus pixels in the image plane form a continuous region. By adjusting the object distance to the lens, a series of defocused (part-in-focus) images could be obtained.</p
A multi-focus image fusion method via region mosaicking on Laplacian pyramids - Fig 7
<p>Illustration of quantitative evaluation (a) RMSE and (b) SSIM under different DBRG radius for the focus region mask segmentation. (c) RMSE and (d) SSIM with different pyramid layers. (e) and (f) are comparisons of nine methods.</p
Illustration of RMLP with two multi-focus images and three pyramid layers.
<p>Illustration of RMLP with two multi-focus images and three pyramid layers.</p
Illustration of the S1 Dataset and its fusion results.
<p>(a)-(f) are six random sampled examples from fifty multi-focus images, (g) is the mask image with only EOF measurement, (h) is the mask image with the proposed DBRG segmentation algorithm. (i) is the fusion result of the Laplacian pyramid (LP) method [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0191085#pone.0191085.ref011" target="_blank">11</a>] and (j)is the fusion result of the proposed RMLP.</p
Wet-Spun Continuous Graphene Films
Macroscopic
assembled, self-standing graphene and graphene oxide
(GO) films have been demonstrated as promising materials in many emerging
fields, such as Li ion battery electrodes, supercapacitors, heat spreaders,
gas separation, and water desalination. Such films were mainly available
on centimeter-scale via the time- and energy-consuming vacuum-filtration
method, which seriously impedes their progress and large-scale applications.
Due to the incompatibility between large-scale and ordered assembly
structures, it remains a big challenge to access large-area assembled
graphene thick films. Here, we report for the first time a fast wet-spinning
assembly strategy to produce continuous GO and graphene thick films.
A 20 m long, 5 cm wide, well-defined GO film was readily achieved
at a speed of 1 m min<sup>–1</sup>. The continuous, strong
GO films were easily woven into bamboo-mat-like fabrics and scrolled
into highly flexible continuous fibers. The reduced graphene films
with high thermal and moderate electrical conductivities were directly
used as fast-response deicing electrothermal mats. The fast yet controllable
wet-spinning assembly approach paves the way for industrial-scale
utilization of graphene