scholarly journals Pansharpening with a Gradient Domain GIF Based on NSST

Electronics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 229
Author(s):  
Jiao Jiao ◽  
Lingda Wu
Keyword(s):  
High Frequency ◽  
Low Frequency ◽  
Fusion Rule ◽  
Objective Evaluation ◽  
Data Sets ◽  
Multi Scale ◽  
Guided Image Filter ◽  
Gradient Domain ◽  
Spatial Quality

In order to improve the fusion quality of multispectral (MS) and panchromatic (PAN) images, a pansharpening method with a gradient domain guided image filter (GIF) that is based on non-subsampled shearlet transform (NSST) is proposed. First, multi-scale decomposition of MS and PAN images is performed by NSST. Second, different fusion rules are designed for high- and low-frequency coefficients. A fusion rule that is based on morphological filter-based intensity modulation (MFIM) technology is proposed for the low-frequency coefficients, and the edge refinement is carried out based on a gradient domain GIF to obtain the fused low-frequency coefficients. For the high-frequency coefficients, a fusion rule based on an improved pulse coupled neural network (PCNN) is adopted. The gradient domain GIF optimizes the firing map of the PCNN model, and then the fusion decision map is calculated to guide the fusion of the high-frequency coefficients. Finally, the fused high- and low-frequency coefficients are reconstructed with inverse NSST to obtain the fusion image. The proposed method was tested using the WorldView-2 and QuickBird data sets; the subjective visual effects and objective evaluation demonstrate that the proposed method is superior to the state-of-the-art pansharpening methods, and it can efficiently improve the spatial quality and spectral maintenance.

The Research on Multiscale Image Fusion Based on the Dualtree Complex Wavelet

2013 ◽  
Vol 748 ◽  
pp. 600-604
Author(s):  
Yi Luo ◽  
Gui Ling Yao ◽  
Wei Fan Wang
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Fusion Rule ◽  
Input Image ◽  
Image Similarity ◽  
Source Image ◽  
Multi Scale ◽  
Rapid Extraction ◽  
Fusion Coefficient

In order to effectively ease and solve fusion effect and the contradiction of the algorithm complexity, this paper puts forward a fusion rule on rapid extraction of multi-scale fusion coefficient, this fusion rules first used in the source image multi-scale decomposition of the scale fusion is the extraction of coefficient based on the neighborhood the fusion of window way, the low frequency of the improved neighborhood entropy to extract matching measure (that is, between the input image similarity degree), high frequency with the cross scale neighborhood gradient to extract matching measure, and gives the fusion coefficient formula. Because of the wavelet transform has moved degeneration, this paper puts forward the application of double tree after wavelet transform to do image multi-scale decomposition.

scholarly journals CHANGE DETECTION OF REMOTE SENSING IMAGES BY DT-CWT AND MRF

2017 ◽  
Vol XLII-1/W1 ◽  
pp. 3-10
Author(s):  
S. Ouyang ◽  
K. Fan ◽  
H. Wang ◽  
Z. Wang
Keyword(s):  
Remote Sensing ◽  
Change Detection ◽  
High Frequency ◽  
Low Frequency ◽  
Fusion Rule ◽  
Significant Loss ◽  
Segmentation Algorithm ◽  
Complex Wavelet Transform ◽  
Difference Image ◽  
Multi Scale

Aiming at the significant loss of high frequency information during reducing noise and the pixel independence in change detection of multi-scale remote sensing image, an unsupervised algorithm is proposed based on the combination between Dual-tree Complex Wavelet Transform (DT-CWT) and Markov random Field (MRF) model. This method first performs multi-scale decomposition for the difference image by the DT-CWT and extracts the change characteristics in high-frequency regions by using a MRF-based segmentation algorithm. Then our method estimates the final maximum a posterior (MAP) according to the segmentation algorithm of iterative condition model (ICM) based on fuzzy c-means(FCM) after reconstructing the high-frequency and low-frequency sub-bands of each layer respectively. Finally, the method fuses the above segmentation results of each layer by using the fusion rule proposed to obtain the mask of the final change detection result. The results of experiment prove that the method proposed is of a higher precision and of predominant robustness properties.

Infrared and visible image fusion method based on rolling guidance filter and NSST

2019 ◽  
Vol 17 (06) ◽  
pp. 1950045 ◽  
Author(s):  
Cheng Zhao ◽  
Yongdong Huang
Keyword(s):  
Image Fusion ◽  
High Frequency ◽  
Low Frequency ◽  
Fusion Rule ◽  
Fusion Method ◽  
Visible Image ◽  
Guided Filtering ◽  
Gradient Domain ◽  
Visible Images ◽  
Image Fusion Method

The rolling guidance filtering (RGF) has a good characteristic which can smooth texture and preserve the edges, and non-subsampled shearlet transform (NSST) has the features of translation invariance and direction selection based on which a new infrared and visible image fusion method is proposed. Firstly, the rolling guidance filter is used to decompose infrared and visible images into the base and detail layers. Then, the NSST is utilized on the base layer to get the high-frequency coefficients and low-frequency coefficients. The fusion of low-frequency coefficients uses visual saliency map as a fusion rule, and the coefficients of the high-frequency subbands use gradient domain guided filtering (GDGF) and improved Laplacian sum to fuse coefficients. Finally, the fusion of the detail layers combines phase congruency and gradient domain guided filtering as the fusion rule. As a result, the proposed method can not only extract the infrared targets, but also fully preserves the background information of the visible images. Experimental results indicate that our method can achieve a superior performance compared with other fusion methods in both subjective and objective assessments.

Dynamics of the processes in metal machining

1998 ◽  
Vol 2 ◽  
pp. 115-122
Author(s):  
Donatas Švitra ◽  
Jolanta Janutėnienė
Keyword(s):  
High Frequency ◽  
Machine Tools ◽  
Metal Cutting ◽  
Cutting Tool ◽  
Low Frequency ◽  
Metal Cutting Machine ◽  
Cutting Machine ◽  
Metal Machining

In the practice of processing of metals by cutting it is necessary to overcome the vibration of the cutting tool, the processed detail and units of the machine tool. These vibrations in many cases are an obstacle to increase the productivity and quality of treatment of details on metal-cutting machine tools. Vibration at cutting of metals is a very diverse phenomenon due to both it’s nature and the form of oscillatory motion. The most general classification of vibrations at cutting is a division them into forced vibration and autovibrations. The most difficult to remove and poorly investigated are the autovibrations, i.e. vibrations arising at the absence of external periodic forces. The autovibrations, stipulated by the process of cutting on metalcutting machine are of two types: the low-frequency autovibrations and high-frequency autovibrations. When the low-frequency autovibration there appear, the cutting process ought to be terminated and the cause of the vibrations eliminated. Otherwise, there is a danger of a break of both machine and tool. In the case of high-frequency vibration the machine operates apparently quiently, but the processed surface feature small-sized roughness. The frequency of autovibrations can reach 5000 Hz and more.

scholarly journals Integration of Satellite Data with High Resolution Ratio: Improvement of Spectral Quality with Preserving Spatial Details

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4418 ◽  
Author(s):  
Aleksandra Sekrecka ◽  
Michal Kedzierski
Keyword(s):  
High Ratio ◽  
Data Sets ◽  
Spectral Quality ◽  
Local Statistics ◽  
Panchromatic Image ◽  
Urbanized Area ◽  
Fusion Methods ◽  
Spatial Quality ◽  
Different Levels

Commonly used image fusion techniques generally produce good results for images obtained from the same sensor, with a standard ratio of spatial resolution (1:4). However, an atypical high ratio of resolution reduces the effectiveness of fusion methods resulting in a decrease in the spectral or spatial quality of the sharpened image. An important issue is the development of a method that allows for maintaining simultaneous high spatial and spectral quality. The authors propose to strengthen the pan-sharpening methods through prior modification of the panchromatic image. Local statistics of the differences between the original panchromatic image and the intensity of the multispectral image are used to detect spatial details. The Euler’s number and the distance of each pixel from the nearest pixel classified as a spatial detail determine the weight of the information collected from each integrated image. The research was carried out for several pan-sharpening methods and for data sets with different levels of spectral matching. The proposed solution allows for a greater improvement in the quality of spectral fusion, while being able to identify the same spatial details for most pan-sharpening methods and is mainly dedicated to Intensity-Hue-Saturation based methods for which the following improvements in spectral quality were achieved: about 30% for the urbanized area and about 15% for the non-urbanized area.

scholarly journals Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

2014 ◽  
Vol 14 (2) ◽  
pp. 102-108 ◽  
Author(s):  
Yong Yang ◽  
Shuying Huang ◽  
Junfeng Gao ◽  
Zhongsheng Qian
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Objective Evaluation ◽  
Discrete Wavelet ◽  
Evaluation Indexes ◽  
Fused Image ◽  
Focus Image

Abstract In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.

Mind–body interactive qigong improves physical and mental aspects of quality of life in inpatients with stroke: A randomized control study

2019 ◽  
Vol 18 (8) ◽  
pp. 658-666 ◽  
Author(s):  
Ching-Hsiang Chen ◽  
Kuo-Sheng Hung ◽  
Yu-Chu Chung ◽  
Mei-Ling Yeh
Keyword(s):  
Quality Of Life ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
High Frequency ◽  
Standard Care ◽  
Low Frequency ◽  
Control Group ◽  
Subacute Stroke ◽  
Interactive Exercise

Background: Stroke, a medical condition that causes physical disability and mental health problems, impacts negatively on quality of life. Post-stroke rehabilitation is critical to restoring quality of life in these patients. Objectives: This study was designed to evaluate the effect of a mind–body interactive qigong intervention on the physical and mental aspects of quality of life, considering bio-physiological and mental covariates in subacute stroke inpatients. Methods: A randomized controlled trial with repeated measures design was used. A total of 68 participants were recruited from the medical and rehabilitation wards at a teaching hospital in northern Taiwan and then randomly assigned either to the Chan-Chuang qigong group, which received standard care plus a 10-day mind–body interactive exercise program, or to the control group, which received standard care only. Data were collected using the National Institutes of Health Stroke Scale, Hospital Anxiety and Depression Scale, Short Form-12, stroke-related neurologic deficit, muscular strength, heart rate variability and fatigue at three time points: pre-intervention, halfway through the intervention (day 5) and on the final day of the intervention (day 10). Results: The results of the mixed-effect model analysis showed that the qigong group had a significantly higher quality of life score at day 10 ( p<0.05) than the control group. Among the covariates, neurologic deficit ( p=0.04), muscle strength ( p=0.04), low frequency to high frequency ratio ( p=0.02) and anxiety ( p=0.04) were significantly associated with changes in quality of life. Conversely, heart rate, heart rate variability (standard deviation of normal-to-normal intervals, low frequency and high frequency), fatigue and depression were not significantly associated with change in quality of life ( p >0.05). Conclusions: This study supports the potential benefits of a 10-day mind–body interactive exercise (Chan-Chuang qigong) program for subacute stroke inpatients and provides information that may be useful in planning adjunctive rehabilitative care for stroke inpatients.

scholarly journals Effect of Closed-Loop Vibration Stimulation on Heart Rhythm during Naps

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4136 ◽  
Author(s):  
Sang Ho Choi ◽  
Heenam Yoon ◽  
Hyung Won Jin ◽  
Hyun Bin Kwon ◽  
Seong Min Oh ◽  
...  
Keyword(s):  
High Frequency ◽  
Closed Loop ◽  
Low Frequency ◽  
Heart Rhythm ◽  
Quality Of Sleep ◽  
Stimulation Condition ◽  
Term Basis ◽  
Stimulation System

Sleep plays a primary function for health and sustains physical and cognitive performance. Although various stimulation systems for enhancing sleep have been developed, they are difficult to use on a long-term basis. This paper proposes a novel stimulation system and confirms its feasibility for sleep. Specifically, in this study, a closed-loop vibration stimulation system that detects the heart rate (HR) and applies −n% stimulus beats per minute (BPM) computed on the basis of the previous 5 min of HR data was developed. Ten subjects participated in the evaluation experiment, in which they took a nap for approximately 90 min. The experiment comprised one baseline and three stimulation conditions. HR variability analysis showed that the normalized low frequency (LF) and LF/high frequency (HF) parameters significantly decreased compared to the baseline condition, while the normalized HF parameter significantly increased under the −3% stimulation condition. In addition, the HR density around the stimulus BPM significantly increased under the −3% stimulation condition. The results confirm that the proposed stimulation system could influence heart rhythm and stabilize the autonomic nervous system. This study thus provides a new stimulation approach to enhance the quality of sleep and has the potential for enhancing health levels through sleep manipulation.

AN IMAGE FUSION FRAMEWORK BASED ON HUMAN VISUAL SYSTEM IN FRAMELET DOMAIN

2012 ◽  
Vol 10 (01) ◽  
pp. 1250002 ◽  
Author(s):  
GAURAV BHATNAGAR ◽  
Q. M. JONATHAN WU
Keyword(s):  
Visual System ◽  
Image Fusion ◽  
Human Visual System ◽  
High Frequency ◽  
Evaluation Criteria ◽  
Low Frequency ◽  
Weighted Average ◽  
Objective Evaluation ◽  
Fusion Algorithm ◽  
Frequency Bands

In this paper, a novel image fusion algorithm based on framelet transform is presented. The core idea is to decompose all the images to be fused into low and high-frequency bands using framelet transform. For fusion, two different selection strategies are developed and used for low and high-frequency bands. The first strategy is adaptive weighted average based on local energy and is applied to fuse the low-frequency bands. In order to fuse high-frequency bands, a new strategy is developed based on texture while exploiting the human visual system characteristics, which can preserve more details in source images and further improve the quality of fused image. Experimental results demonstrate the efficiency and better performance than existing image fusion methods both in visual inspection and objective evaluation criteria.

Stereoscopic Images Enhancement Based on Edge Sharpening of Wavelet Coefficients

2014 ◽  
Vol 511-512 ◽  
pp. 490-494 ◽  
Author(s):  
Yi Min Qiu ◽  
Shi Hong Chen ◽  
Yi Zhou ◽  
Xin Hai Liu
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Subjective Assessment ◽  
Wavelet Coefficients ◽  
Stereoscopic Images ◽  
Multi Scale ◽  
Image Edge ◽  
Frequency Approximation ◽  
Edge Sharpening

This paper proposed a new image enhancement algorithm based on edge sharpening of wavelet coefficients for stereoscopic images. Our scheme uses the multi-scale characteristic of wavelet transform, decomposes the original image into low frequency approximation sub-graph and several high frequency direction. Under the multi-scale, the low frequency approximation sub-graph is processed by edge sharpening method. Then the low frequency sub-graph decomposes in multi-scale again. At last, the low frequency approximation graph after four layers decompose sharpening and the high frequency approximation of the decomposed sub-graph will be refactored to get the new image. Experimental results show that whether PSNR or visual effect, or the subjective assessment of the DMOS value, the proposed method has better enhanced performance than the conventional edge sharpening and wavelet transform. And it has good image edge enhancement, details protection. Meanwhile, the proposed algorithm has the same computational complexity with wavelet transform.

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