Development of a mass model in estimating weight-wise particle size distribution using digital image processing

Particle size distribution of coarse aggregates through mechanical sieving gives results in terms of cumu- lative mass percent. But digital image processing generated size distribution of particles, while being fast and accurate, is often expressed in terms of area function or number of particles. In this paper, a mass model is developed which converts the image obtained size distribution to mass-wise distribution, mak- ing it readily comparable to mechanical sieving data. The concept of weight/particle ratio is introduced for mass reconstruction from 2D images of particle aggregates. Using this mass model, the effects of several particle shape parameters （such as major axis, minor axis, and equivalent diameter） on sieve-size of the particles is studied. It is shown that the sieve-size of a particle strongly depend upon the shape param- eters, 91% of its variation being explained by major axis, minor axis, bounding box length and equivalent diameter. Furthermore, minor axis gives an overall accurate estimate of particle sieve-size, error in mean size （D-50） being just 0.4%. However, sieve-size of smaller particles （〈20 ram） strongly depends upon the length of the smaller arm of the bounding box enclosing them and sieve-sizes of larger particles （〉20 mm） are highly correlated to their equivalent diameters. Multiple linear regression analysis has been used to generate overall mass-wise particle size distribution, considering the influences of all these shape parameters on particle sieve-size. Multiple linear regression generated overall mass-wise particle size distribution shows a strong correlation with sieve generated data. The adjusted R-square value of the regression analysis is found to be 99 percent （w.r,t cumulative frequency）. The method proposed in this paper provides a time-efficient way of producing accurate （up to 99%） mass-wise PSD using digital image processing and it can be used effectively to renlace the mechanical sieving.

A gray-natural logarithm ratio bilateral filtering method for image processing

A new method based on gray-natural logarithm ratio bilateral filtering is presented for image smoothing in this work. A new gray-natural logarithm ratio range filter kernel, leading to adaptive magnitude from image gray distinction information, is pointed out for the bilateral filtering. The new method can not only well restrain noise but also keep much more weak edges and details of an image, and preserve the original color transition of color images. Experimental results show the effectiveness for image denoising with our method.

Simple and effective method to improve the signal-to-noise ratio of compressive imaging

This Letter presents a simple and effective method to improve the signal-to-noise ratio（SNR） of compressing imaging. The main principles of the proposed method are the correlation of the image signals and the randomness of the noise. Multiple low SNR images are reconstructed firstly by the compressed sensing reconstruction algorithm, and then two-dimensional time delay integration technology is adopted to improve the SNR. Results show that the proposed method can improve the SNR performance efficiently and it is easy to apply the a lgorithm to the real project.

Imaging process and signal-to-noise ratio improvement of enhanced self-heterodyne synthetic aperture imaging ladar

This Letter gives the general construction of an enhanced self-heterodyne synthetic aperture imaging ladar（SAIL） system, and proposes the principle of image processing. A point target is reconstructed in the enhanced self-heterodyne SAIL as well as in down-looking SAIL experiments, and the achieved imaging resolution of the enhanced self-heterodyne SAIL is analyzed. The signal-to-noise ratio（SNR） of the point target final image in the enhanced self-heterodyne SAIL is higher than that in the down-looking SAIL. The enhanced self-heterodyne SAIL can improve the SNR of the target image in far-distance imaging, with practicality.

Assessing chromatin condensation for epigenetics with a DNA-targeting sensor by FRET and FLIM techniques

Here we propose a fluorescent sensor,Chroma-V,consisted of a Hoechst ligand(Hoe) to target chromatin DNA and a BODIPY rotor(BDP) to sense the local viscosity that reflects chromatin condensation state.Within Chroma-V,efficient FRET process from Hoe to BDP facilitated a single-excitation ratiometric imaging of nucleus DNA under fluorescence confocal microscope,which utilized the ratio of two channels to enable an intuitive visualization of chromatin condensation state.And fluorescence lifetime imaging(FLIM) based on fluorescent signal from BDP proved to be a more accurate method to quantify the changes of chromatin condensation state under different epigenetic states,including histone acetylation regulated by deacetylase inhibitors,cell apoptosis induced by DNA-bining drugs,and the epithelialmesenchymal transition of HUVEC cells induced by TGF-β.