Pre-Processing of Hyperspectral Images Using Nonlinear Filters

2013 ◽  
Vol 11 (1) ◽  
pp. 8-13
Author(s):  
V. Behar ◽  
V. Bogdanova
Keyword(s):  
Signal To Noise Ratio ◽  
Correlation Coefficients ◽  
Hyperspectral Images ◽  
Spectral Correlation ◽  
Edge Preserving ◽  
Improvement Factor ◽  
Filter Output ◽  
Average Improvement ◽  
Processing Procedure

Abstract In this paper the use of a set of nonlinear edge-preserving filters is proposed as a pre-processing stage with the purpose to improve the quality of hyperspectral images before object detection. The capability of each nonlinear filter to improve images, corrupted by spatially and spectrally correlated Gaussian noise, is evaluated in terms of the average Improvement factor in the Peak Signal to Noise Ratio (IPSNR), estimated at the filter output. The simulation results demonstrate that this pre-processing procedure is efficient only in case the spatial and spectral correlation coefficients of noise do not exceed the value of 0.6

scholarly journals Quality Metrics Evaluation of Hyperspectral Images

2014 ◽  
Vol XL-8 ◽  
pp. 1221-1226 ◽  
Author(s):  
A. K. Singh ◽  
H. V. Kumar ◽  
G. R. Kadambi ◽  
J. K. Kishore ◽  
J. Shuttleworth ◽  
...  
Keyword(s):  
Hyperspectral Image ◽  
Signal To Noise Ratio ◽  
Principal Component ◽  
Quality Parameters ◽  
Quality Metrics ◽  
Hyperspectral Data ◽  
Hyperspectral Images ◽  
Error Ratio ◽  
Classified Image

In this paper, the quality metrics evaluation on hyperspectral images has been presented using k-means clustering and segmentation. After classification the assessment of similarity between original image and classified image is achieved by measurements of image quality parameters. Experiments were carried out on four different types of hyperspectral images. Aerial and spaceborne hyperspectral images with different spectral and geometric resolutions were considered for quality metrics evaluation. Principal Component Analysis (PCA) has been applied to reduce the dimensionality of hyperspectral data. PCA was ultimately used for reducing the number of effective variables resulting in reduced complexity in processing. In case of ordinary images a human viewer plays an important role in quality evaluation. Hyperspectral data are generally processed by automatic algorithms and hence cannot be viewed directly by human viewers. Therefore evaluating quality of classified image becomes even more significant. An elaborate comparison is made between k-means clustering and segmentation for all the images by taking Peak Signal-to-Noise Ratio (PSNR), Mean Square Error (MSE), Maximum Squared Error, ratio of squared norms called L2RAT and Entropy. First four parameters are calculated by comparing the quality of original hyperspectral image and classified image. Entropy is a measure of uncertainty or randomness which is calculated for classified image. Proposed methodology can be used for assessing the performance of any hyperspectral image classification techniques.

Image Quality Enhancing by Efficient Histogram Equalization

2014 ◽  
Vol 2 (2) ◽  
pp. 47-58
Author(s):  
Ismail Sh. Baqer
Keyword(s):  
Image Quality ◽  
Contrast Enhancement ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Histogram Equalization ◽  
Gray Level ◽  
Signal To Noise ◽  
Squared Error ◽  
Noise Ratio

A two Level Image Quality enhancement is proposed in this paper. In the first level, Dualistic Sub-Image Histogram Equalization DSIHE method decomposes the original image into two sub-images based on median of original images. The second level deals with spikes shaped noise that may appear in the image after processing. We presents three methods of image enhancement GHE, LHE and proposed DSIHE that improve the visual quality of images. A comparative calculations is being carried out on above mentioned techniques to examine objective and subjective image quality parameters e.g. Peak Signal-to-Noise Ratio PSNR values, entropy H and mean squared error MSE to measure the quality of gray scale enhanced images. For handling gray-level images, convenient Histogram Equalization methods e.g. GHE and LHE tend to change the mean brightness of an image to middle level of the gray-level range limiting their appropriateness for contrast enhancement in consumer electronics such as TV monitors. The DSIHE methods seem to overcome this disadvantage as they tend to preserve both, the brightness and contrast enhancement. Experimental results show that the proposed technique gives better results in terms of Discrete Entropy, Signal to Noise ratio and Mean Squared Error values than the Global and Local histogram-based equalization methods

Singular Values Decomposition and Lifting Wavelet Transform for Speech Signal Embedding into Digital Image

2019 ◽  
Vol 12 (2) ◽  
pp. 138-151
Author(s):  
Mourad Talbi ◽  
Med Salim Bouhlel
Keyword(s):  
Wavelet Transform ◽  
Speech Signal ◽  
Signal To Noise Ratio ◽  
Perceptual Quality ◽  
Lifting Wavelet Transform ◽  
Signal To Noise ◽  
Perceptual Evaluation ◽  
Lifting Wavelet ◽  
Noise Ratio

Background: In this paper, we propose a secure image watermarking technique which is applied to grayscale and color images. It consists in applying the SVD (Singular Value Decomposition) in the Lifting Wavelet Transform domain for embedding a speech image (the watermark) into the host image. Methods: It also uses signature in the embedding and extraction steps. Its performance is justified by the computation of PSNR (Pick Signal to Noise Ratio), SSIM (Structural Similarity), SNR (Signal to Noise Ratio), SegSNR (Segmental SNR) and PESQ (Perceptual Evaluation Speech Quality). Results: The PSNR and SSIM are used for evaluating the perceptual quality of the watermarked image compared to the original image. The SNR, SegSNR and PESQ are used for evaluating the perceptual quality of the reconstructed or extracted speech signal compared to the original speech signal. Conclusion: The Results obtained from computation of PSNR, SSIM, SNR, SegSNR and PESQ show the performance of the proposed technique.

scholarly journals The quality of life in Chinese juvenile idiopathic arthritis patients: psychometric properties of the pediatric quality of life inventor generic core scales and rheumatology module

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Hua-hong Wu ◽  
Feng-qi Wu ◽  
Yang Li ◽  
Jian-ming Lai ◽  
Gai-xiu Su ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Juvenile Idiopathic Arthritis ◽  
Reliability And Validity ◽  
Correlation Coefficients ◽  
Active Period ◽  
Generic Core Scale ◽  
Remission Period ◽  
Pedsql 4.0 ◽  
The Mean

Abstract Background Juvenile idiopathic arthritis (JIA) may seriously affects patients’ quality of life (QoL), but it was rarely focused and studied in China, so we explore JIA children’s QoL using Chinese version of the PedsQL4.0 Generic Core and PedsQL3.0 Rheumatology Module scale, and analyzed the psychometric properties of these two Scales among Chinese JIA children. Methods We recruited 180 JIA patients from Children's Hospital Affiliated to Capital Institute of Pediatrics and Hebei Yanda Hospital from July 2018 to August 2019. The questionnaires include information related on JIA, PedsQL4.0 generic core and PedsQL3.0 Rheumatology Module scales. According to the disease type, onset age of and course of JIA, we divided them into different groups, then compared the QoL status among different groups. Moreover, we analyzed the reliability and validity of these two scales in these 180 JIA children. Results The mean score of PedsQL4.0 generic core scale on these 180 patients was 82.85 ± 14.82, for these in active period was 72.05 ± 15.29, in remission period was 89.77 ± 9.23; the QoL score of systemic, polyarticular and oligoarticular JIA patients were 77.05 ± 19.11, 84.33 ± 12.46 and 87.12 ± 10.23. The mean score of PedsQL3.0 Rheumatology Module scale on 180 patients was 91.22 ± 9.45, for these in active period was 84.70 ± 11.37, in remission period was 95.43 ± 4.48; the QoL score of systemic, polyarticular and oligoarticular JIA patients were 89.41 ± 11.54, 89.38 ± 10.08 and 93.71 ± 6.92. In the PedsQL 4.0 Generic Core scale, the α coefficients of total scale and almost every dimension are all greater than 0.8 except for the school activity dimension of 0.589; the correlation coefficients of 22 items’ scores (total 23 items) with the scores of dimensions they belong to are greater than 0.5 (maximum value is 0.864), and the other one is 0.406. In PedsQL3.0 Rheumatology Module scale, except for the treatment and worry dimensions of 0.652 and 0.635, the α coefficients of other dimensions and the total scale are all greater than 0.7; the correlation coefficients of all items’ score were greater than 0.5 (the maximum is 0.933, the minimum is 0.515). Conclusions The QoL of Chinese JIA children is worse than their healthy peers, these in active period and diagnosed as systemic type were undergoing worst quality of life. The reliability and validity of PedsQL 4.0 Generic Core and PedsQL3.0 Rheumatology Module scale in Chinese JIA children are satisfactory, and can be used in clinical and scientific researches.

scholarly journals 3D DCT Based Image Compression Method for the Medical Endoscopic Application

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1817
Author(s):  
Jiawen Xue ◽  
Li Yin ◽  
Zehua Lan ◽  
Mingzhu Long ◽  
Guolin Li ◽  
...  
Keyword(s):  
Image Compression ◽  
Compression Ratio ◽  
Signal To Noise Ratio ◽  
Blocking Artifacts ◽  
Compression Method ◽  
High Compression Ratio ◽  
Multiplication Operation ◽  
3D Data ◽  
Wireless Capsule

This paper proposes a novel 3D discrete cosine transform (DCT) based image compression method for medical endoscopic applications. Due to the high correlation among color components of wireless capsule endoscopy (WCE) images, the original 2D Bayer data pattern is reconstructed into a new 3D data pattern, and 3D DCT is adopted to compress the 3D data for high compression ratio and high quality. For the low computational complexity of 3D-DCT, an optimized 4-point DCT butterfly structure without multiplication operation is proposed. Due to the unique characteristics of the 3D data pattern, the quantization and zigzag scan are ameliorated. To further improve the visual quality of decompressed images, a frequency-domain filter is proposed to eliminate the blocking artifacts adaptively. Experiments show that our method attains an average compression ratio (CR) of 22.94:1 with the peak signal to noise ratio (PSNR) of 40.73 dB, which outperforms state-of-the-art methods.

scholarly journals Understanding PI-QUAL for prostate MRI quality: a practical primer for radiologists

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Francesco Giganti ◽  
Alex Kirkham ◽  
Veeru Kasivisvanathan ◽  
Marianthi-Vasiliki Papoutsaki ◽  
Shonit Punwani ◽  
...  
Keyword(s):  
Diffusion Weighted Imaging ◽  
Signal To Noise Ratio ◽  
High Signal ◽  
Diagnostic Quality ◽  
Prostate Mri ◽  
Prostate Imaging ◽  
Dynamic Contrast Enhanced ◽  
Diffusion Weighted ◽  
Contrast Enhanced

AbstractProstate magnetic resonance imaging (MRI) of high diagnostic quality is a key determinant for either detection or exclusion of prostate cancer. Adequate high spatial resolution on T2-weighted imaging, good diffusion-weighted imaging and dynamic contrast-enhanced sequences of high signal-to-noise ratio are the prerequisite for a high-quality MRI study of the prostate. The Prostate Imaging Quality (PI-QUAL) score was created to assess the diagnostic quality of a scan against a set of objective criteria as per Prostate Imaging-Reporting and Data System recommendations, together with criteria obtained from the image. The PI-QUAL score is a 1-to-5 scale where a score of 1 indicates that all MR sequences (T2-weighted imaging, diffusion-weighted imaging and dynamic contrast-enhanced sequences) are below the minimum standard of diagnostic quality, a score of 3 means that the scan is of sufficient diagnostic quality, and a score of 5 implies that all three sequences are of optimal diagnostic quality. The purpose of this educational review is to provide a practical guide to assess the quality of prostate MRI using PI-QUAL and to familiarise the radiologist and all those involved in prostate MRI with this scoring system. A variety of images are also presented to demonstrate the difference between suboptimal and good prostate MR scans.

Using spatial information for evaluating the quality of prediction maps from hyperspectral images: A geostatistical approach

2019 ◽  
Vol 1077 ◽  
pp. 116-128 ◽  
Author(s):  
Ana Herrero-Langreo ◽  
Nathalie Gorretta ◽  
Bruno Tisseyre ◽  
Aoife Gowen ◽  
Jun-Li Xu ◽  
...  
Keyword(s):  
Spatial Information ◽  
Hyperspectral Images ◽  
Geostatistical Approach

Optimal Parameter Design of Solder Residue in Flip Chip Process by Using Taguchi Method

2010 ◽  
Vol 443 ◽  
pp. 543-548
Author(s):  
Jian Long Kuo ◽  
Kai Lun Chao ◽  
Chun Cheng Kuo
Keyword(s):  
Taguchi Method ◽  
Product Quality ◽  
Manufacturing Process ◽  
Flip Chip ◽  
Optimal Parameter ◽  
Experimental Testing ◽  
Signal To Noise Ratio ◽  
Optimal Solution ◽  
Passive Component

Because the solder residue was found in the manufacturing process which greatly affected the product quality, the purpose of this paper was to make the product quality improved and to find an optimal solution for process parameters in the flip chip process. The experimental testing was based on SMT manufacturing process. The amount and size of solder left on passive component in the process of manufacturing were considered as the quality traits. Since too many solders left on the passive component side during flux cleaning process, it was possible that the balling would be flowed into the chip, which caused the bump short in the chip and affected the quality of the product. In this paper, orthogonal array by using Taguchi method is adopted as the effective experimental method with the least experimental runs. Also, based on the quality evaluation of signal-to-noise ratio, the ANOVA is used to evaluate the effects of quality target according to the experimental results. The results reveal that the optimization in the process is confirmed. Therefore, this study can effectively improve the solder residue in semiconductor manufacturing process.

Depression and Inflammatory Markers in Veterans With Multiple Sclerosis

2021 ◽  
pp. 109980042110500
Author(s):  
Pamela Newland ◽  
Yelyzaveta Basan ◽  
Ling Chen ◽  
Gregory Wu
Keyword(s):  
Multiple Sclerosis ◽  
Inflammatory Markers ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
The United States ◽  
Biological Mechanisms ◽  
The Central Nervous System ◽  
Brain And Spinal Cord ◽  
The Brain

Multiple sclerosis (MS), an inflammatory neurodegenerative disease of the central nervous system (CNS), afflicts over one per thousand people in the United States. The pathology of MS typically involves lesions in several regions, including the brain and spinal cord. The manifestation of MS is variable and carries great potential to negatively impact quality of life (QOL). Evidence that inflammatory markers are related to depression in MS is accumulating. However, there are barriers in precisely identifying the biological mechanisms underlying depression and inflammation. Analysis of cytokines provides one promising approach for understanding the mechanisms that may contribute to MS symptoms. Methods: In this pilot study, we measured salivary levels of interleukin (IL)-6, IL-1beta (β), and IL-10 in 24 veterans with MS. Descriptive statistics were reported and Pearson correlation coefficients were obtained between cytokines and depression. Results: The anti-inflammatory cytokine IL-10 was significantly negatively associated with depression in veterans with MS (r = −0.47, p = .024). Conclusion: Cytokines may be useful for elucidating biological mechanisms associated with the depression and a measure for nurses caring for veterans with MS.

scholarly journals Correlations Between Clinical Trial Outcomes Based on Symptoms, Functional Impairments, and Quality of Life in Children and Adolescents With ADHD

2017 ◽  
Vol 23 (13) ◽  
pp. 1578-1591 ◽  
Author(s):  
David R. Coghill ◽  
Alain Joseph ◽  
Vanja Sikirica ◽  
Mark Kosinski ◽  
Caleb Bliss ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Children And Adolescents ◽  
Rating Scale ◽  
Controlled Trial ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Parent Report ◽  
Functional Impairments ◽  
Risk Avoidance

Objective: To assess relationships between treatment-associated changes in measures of ADHD symptoms, functional impairments, and health-related quality of life in children and adolescents with ADHD. Method: Pearson correlation coefficients were calculated post hoc for changes from baseline to endpoint in outcomes of one randomized, placebo- and active-controlled trial of lisdexamfetamine (osmotic-release methylphenidate reference) and one of guanfacine extended-release (atomoxetine reference). Results: Changes in ADHD Rating Scale IV (ADHD-RS-IV) total score generally correlated moderately with changes in Child Health and Illness Profile−Child Edition: Parent Report Form (CHIP-CE:PRF) Achievement and Risk Avoidance ( r ≈ .4), but weakly with Resilience, Satisfaction, and Comfort ( r ≈ .2); and moderately with Weiss Functional Impairment Rating Scale–Parent (WFIRS-P) total score ( r ≈ .5). CHIP-CE:PRF Achievement and Risk Avoidance correlated moderately to strongly with WFIRS-P total score ( r ≈ .6). Conclusion: The ADHD-RS-IV, CHIP-CE:PRF, and WFIRS-P capture distinct but interconnected aspects of treatment response in individuals with ADHD.

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