Improved Multi Scale DR Medical Image Enhancement Algorithm

2014 ◽  
Vol 530-531 ◽  
pp. 413-417
Author(s):  
Xiao Jing Sun ◽  
Ai Bin Chen
Keyword(s):  
Image Enhancement ◽  
Low Frequency ◽  
Frequency Component ◽  
Image Feature ◽  
High Frequency Component ◽  
Image Processing Algorithm ◽  
Multi Scale ◽  
Gaussian Pyramid ◽  
Layer Image ◽  
Enhancement Algorithm

The original DR image is decomposed into different scale and frequency of the band image sequence by using Laplace gaussian pyramid model methods. Using multi-scale image enhancement algorithm to enhance the High frequency component of the decomposed image, Then adjust the light of the low frequency part to make the reconstructed image illumination contrast more reasonable. The enhanced process according to different frequency layer image feature make the different gain weight for the different frequency layer image characteristics,so different frequency image layer realize respectively noise smoothing, dimensionality reduction and enhance the effect of edge character.The simulation experiments showed that this Image Processing Algorithm effect is very good.

scholarly journals Smart Image Enhancement Using CLAHE Based on an F-Shift Transformation during Decompression

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1374
Author(s):  
Ruiqin Fan ◽  
Xiaoyun Li ◽  
Sanghyuk Lee ◽  
Tongliang Li ◽  
Hao Lan Zhang
Keyword(s):  
Image Enhancement ◽  
Low Frequency ◽  
Histogram Equalization ◽  
Frequency Component ◽  
High Frequency Component ◽  
Enhancement Effect ◽  
Two Dimensional ◽  
Compression Properties ◽  
Contrast Information ◽  
Image Details

As technologies for image processing, image enhancement can provide more effective information for later data mining and image compression can reduce storage space. In this paper, a smart enhancement scheme during decompression, which combined a novel two-dimensional F-shift (TDFS) transformation and a non-standard two-dimensional wavelet transform (NSTW), is proposed. During the decompression, the first coefficient s00 of the wavelet synopsis was used to adaptively adjust the global gray level of the reconstructed image. Next, the contrast-limited adaptive histogram equalization (CLAHE) was used to achieve the enhancement effect. To avoid a blocking effect, CLAHE was used when the synopsis was decompressed to the second-to-last level. At this time, we only enhanced the low-frequency component and did not change the high-frequency component. Lastly, we used CLAHE again after the image reconstruction. Through experiments, the effectiveness of our scheme was verified. Compared with the existing methods, the compression properties were preserved and the image details and contrast could also be enhanced. The experimental results showed that the image contrast, information entropy, and average gradient were greatly improved compared with the existing methods.

A Modified Multi Scale Retinex with Color Restoration Algorithm for Automatic Enhancement of Landsat-5 Remote Sensing Image

2011 ◽  
Vol 341-342 ◽  
pp. 893-897
Author(s):  
Gui Zhou Wang ◽  
Guo Jin He
Keyword(s):  
Image Enhancement ◽  
Dynamic Range ◽  
Color Constancy ◽  
Human Perception ◽  
Histogram Equalization ◽  
Image Processing Algorithm ◽  
Multi Scale ◽  
Dynamic Range Compression ◽  
Restoration Algorithm ◽  
Color Restoration

The retinex is a human perception based image processing algorithm which provides color constancy and dynamic range compression. The multi scale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. But the MSRCR results suffer from lower global brightness and partial color distortion. In order to improve the MSRCR method, this paper presents a modified MSRCR algorithm to Landsat-5 image enhancement considering percent liner stretch and histogram adjustment. Finally, the effect of modified MSRCR method on Landsat-5 image enhancement is analyzed and the comparison with other color adjustment methods such as gamma correction and histogram equalization is reported in the experimental results.

scholarly journals Impaired vagal activity to meal in patients with functional dyspepsia and delayed gastric emptying

2017 ◽  
Vol 46 (2) ◽  
pp. 792-801 ◽  
Author(s):  
W-J Guo ◽  
S-K Yao ◽  
Y-L Zhang ◽  
S-Y Du ◽  
H-F Wang ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Gastric Emptying ◽  
Functional Dyspepsia ◽  
Delayed Gastric Emptying ◽  
Low Frequency ◽  
Treatment Method ◽  
Frequency Component ◽  
High Frequency Component ◽  
Vagal Activity ◽  
Nervous Function

Objective This study was performed to investigate impaired vagal activity to meal in patients with functional dyspepsia (FD) with delayed gastric emptying (GE). Methods Eighty-five patients were studied. GE parameters, including those in the overall and proximal stomach, were measured by GE functional tests at the Department of Nuclear Medicine. Autonomic nervous function was tested by spectral analysis of heart rate variability (HRV). The vagal activity and sympathetic activity were analyzed by recording the power in the high-frequency component (HF), low-frequency component (LF), and LF/HF ratio. Results Overall and proximal GE were delayed in 47.2% and 50.9% of the patients, respectively. Spectral analysis of HRV showed that the HF in patients with delayed proximal GE was significantly lower and that the LF/HF ratio was significantly higher than those in patients with normal proximal GE after a meal. Conclusion Delayed proximal GE might be caused by disrupted sympathovagal balance as a result of decreased vagal activity after a meal. Improvement in vagal activity may constitute an effective treatment method for patients with FD.

Research on Combined Prediction Model for Busy Telephone Traffic

2014 ◽  
Vol 610 ◽  
pp. 789-796
Author(s):  
Jiang Bao Li ◽  
Zhen Hong Jia ◽  
Xi Zhong Qin ◽  
Lei Sheng ◽  
Li Chen
Keyword(s):  
Prediction Model ◽  
Prediction Accuracy ◽  
Low Frequency ◽  
Prediction Method ◽  
Pso Algorithm ◽  
Frequency Component ◽  
Least Square ◽  
High Frequency Component ◽  
Support Vector ◽  
Telephone Traffic

In order to improve the prediction accuracy of busy telephone traffic, this study proposes a busy telephone traffic prediction method that combines wavelet transformation and least square support vector machine (lssvm) model which is optimized by particle swarm optimization (pso) algorithm. Firstly, decompose the pretreatment of busy telephone traffic data with mallat algorithm and get low frequency component and high frequency component. Secondly, reconfigure each component and use pso_lssvm model predict each reconfigured one. Then the busy telephone traffic can be achieved. The experimental results show that the prediction model has higher prediction accuracy and stability.

scholarly journals STORM INDUCED PERIODICITIES OF SUSPENDED SAND MOVEMENT

1978 ◽  
Vol 1 (16) ◽  
pp. 105 ◽  
Author(s):  
Jay E. Leonard ◽  
Benno M. Brenninkmeyer
Keyword(s):  
Surf Zone ◽  
Normal Wave ◽  
Low Frequency ◽  
Sediment Concentration ◽  
Frequency Component ◽  
High Frequency Component ◽  
Computational Technique ◽  
Electromagnetic Current ◽  
Discrete Fourier Analysis ◽  
Sediment Movement

An array of electronic sensors was installed on Nauset Light Beach, Cape Cod, Massachusetts, U.S.A., in order to provide a description of the sediment movement during storm conditions. These sensors included two sediment concentration indicators (almometers) which monitor sediment movement as a function of elevation and time, one bidirectional electromagnetic current meter, and a resistive wave staff. Prior field studies performed during "normal" conditions have indicated that surf-zone suspended sediment movement is a low-frequency phenomenon, with the relatively high-frequency component (normal wave period) contributing little to the amount of total sediment transported. Development of a computational technique based upon discrete Fourier analysis and digital filtering called Spectrally Filtered Integration (SFI) provides the calculation and filtering of true units of sediment change in grams-per-liter. Moreover, the SFI technique eliminates the possibility spurious sediment information created by the presence of air bubbles in the water column. Generally, higher-frequency sediment movement is more common during storm conditions than during normal non-storm conditions. This movement is controlled not by the prevailing wave and swell periods, but by a longer period which may be due to water interactions below the surface.

Gaussian Pyramid Transform Retinex Image Enhancement Algorithm Based on Bilateral Filtering

2020 ◽  
Vol 57 (16) ◽  
pp. 161019
Author(s):  
林昌 Lin Chang ◽  
周海峰 Zhou Haifeng ◽  
陈武 Chen Wu
Keyword(s):  
Image Enhancement ◽  
Bilateral Filtering ◽  
Gaussian Pyramid ◽  
Enhancement Algorithm

scholarly journals Extreme prolongation of expiration breathing: Effects on electroencephalogram and autonomic nervous function

2018 ◽  
Vol 10 (2) ◽  
pp. 62-65
Author(s):  
Teruhisa Komori
Keyword(s):  
High Frequency ◽  
Frequency Ratio ◽  
Low Frequency ◽  
Frequency Component ◽  
Small Sample ◽  
High Frequency Component ◽  
Deep Breathing ◽  
Continuous Eeg ◽  
Nervous Function ◽  
Electrocardiogram Ecg

To clarify the physiological and psychological effects of deep breathing, the effects of extreme prolongation of expiration breathing (Okinaga) were investigated using electroencephalogram (EEG) and electrocardiogram (ECG). Participants were five male Okinaga practitioners in their 50s and 60s. Participants performed Okinaga for 31 minutes while continuous EEG and ECG measurements were taken. After 16 minutes of Okinaga, and until the end of the session, the percentages of theta and alpha 2 waves were significantly higher than at baseline. After 20 minutes, and until the end of the session, the percentage of beta waves was significantly lower than at baseline. The high frequency component of heart rate variability was significantly lower after 12 minutes of Okinaga and lasted until 23 minutes. The low frequency/high frequency ratio was significantly lower after 18 minutes of Okinaga and until the end of the session. Okinaga produced relaxation, suggesting that deep breathing may relieve anxiety. However, study limitations include potential ambiguity in the interpretation of the low frequency/high frequency ratio, the small sample, and the fact that EEG was measured only on the forehead.

scholarly journals Extreme prolongation of expiration breathing: Effects on electroencephalogram and autonomic nervous function

2018 ◽  
Vol 10 (2) ◽  
Author(s):  
Teruhisa Komori
Keyword(s):  
High Frequency ◽  
Frequency Ratio ◽  
Low Frequency ◽  
Frequency Component ◽  
Small Sample ◽  
High Frequency Component ◽  
Deep Breathing ◽  
Continuous Eeg ◽  
Nervous Function ◽  
Electrocardiogram Ecg

To clarify the physiological and psychological effects of deep breathing, the effects of extreme prolongation of expiration breathing (Okinaga) were investigated using electroencephalogram (EEG) and electrocardiogram (ECG). Participants were five male Okinaga practitioners in their 50s and 60s. Participants performed Okinaga for 31 minutes while continuous EEG and ECG measurements were taken. After 16 minutes of Okinaga, and until the end of the session, the percentages of theta and alpha 2 waves were significantly higher than at baseline. After 20 minutes, and until the end of the session, the percentage of beta waves was significantly lower than at baseline. The high frequency component of heart rate variability was significantly lower after 12 minutes of Okinaga and lasted until 23 minutes. The low frequency/high frequency ratio was significantly lower after 18 minutes of Okinaga and until the end of the session. Okinaga produced relaxation, suggesting that deep breathing may relieve anxiety. However, study limitations include potential ambiguity in the interpretation of the low frequency/high frequency ratio, the small sample, and the fact that EEG was measured only on the forehead.

Analysis of the Visual Spectrum of Methyl Orange in Solvents and in Hydrophobic Binding Sites

1973 ◽  
Vol 51 (4) ◽  
pp. 628-635 ◽  
Author(s):  
Richard L. Reeves ◽  
Robert S. Kaiser ◽  
Mary S. Maggio ◽  
Edward A. Sylvestre ◽  
William H. Lawton
Keyword(s):  
Hydrogen Bonding ◽  
Methyl Orange ◽  
Organic Solvents ◽  
Absorption Maximum ◽  
Low Frequency ◽  
Blue Shift ◽  
Frequency Component ◽  
High Frequency Component ◽  
Surfactant Micelle ◽  
Aqueous Solvent

The absorption curves of methyl orange (MO) and analogous p-aminophenylazobenzenes in organic and aqueous organic solvents are shown to consist of two severely overlapping bands. The curves have been resolved into two skewed component bands using a regression method. The blue shift of the absorption maximum obtained when organic solvents are added to aqueous solutions of MO, or when MO is bound to bovine serum albumin or a surfactant micelle, is the result of a change in relative intensities of the component bands. The low-frequency component is assigned to a π1 → π1* transition of a solvate in which there is specific hydrogen-bonding interaction between solvent and the azo nitrogens, and the high-frequency component to a π1 → π1* transition of a solvate in which the interaction is absent. The low-frequency component is favored by aqueous solvent compositions and by low temperatures. The free energies of interconversion of the species in various hydrogen-bonding solvents are correlated by the solvent surface tension but not by the dielectric constant. The results show that the shift in absorption maximum accompanying binding to a protein or micelle should be interpreted as a shift in an equilibrium rather than as a shift in transition energy.

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