Displaying publications 41 - 60 of 78 in total

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  1. Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model
    Sim KS, Wee MY, Lim WK
    Microsc Res Tech, 2008 Oct;71(10):710-20.
    PMID: 18615490 DOI: 10.1002/jemt.20610
    We propose to cascade the Shape-Preserving Piecewise Cubic Hermite model with the Autoregressive Moving Average (ARMA) interpolator; we call this technique the Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average (SP2CHARMA) model. In a few test cases involving different images, this model is found to deliver an optimum solution for signal to noise ratio (SNR) estimation problems under different noise environments. The performance of the proposed estimator is compared with two existing methods: the autoregressive-based and autoregressive moving average estimators. Being more robust with noise, the SP2CHARMA estimator has efficiency that is significantly greater than those of the two methods.
    Matched MeSH terms: Signal-To-Noise Ratio
  2. Image signal-to-noise ratio estimation using the autoregressive model
    Sim KS, Kamel NS
    Scanning, 2004 7 31;26(3):135-9.
    PMID: 15283250
    In the last two decades, a variety of techniques for signal-to-noise ratio (SNR) estimation in scanning electron microscope (SEM) images have been proposed. However, these techniques can be divided into two groups: first, SNR estimators of good accuracy, but based on impractical assumptions; second, estimators based on realistic assumptions but of poor accuracy. In this paper we propose the implementation of autoregressive (AR)-model interpolation as a solution to the problem. Unlike others, the proposed technique is based on a single SEM image and offers the required accuracy and robustness in estimating SNR values.
    Matched MeSH terms: Signal-To-Noise Ratio
  3. Fulltext InNetGAN: Inception Network-Based Generative Adversarial Network for Denoising Low-Dose Computed Tomography
    Kulathilake KASH, Abdullah NA, Bandara AMRR, Lai KW
    J Healthc Eng, 2021;2021:9975762.
    PMID: 34552709 DOI: 10.1155/2021/9975762
    Low-dose Computed Tomography (LDCT) has gained a great deal of attention in clinical procedures due to its ability to reduce the patient's risk of exposure to the X-ray radiation. However, reducing the X-ray dose increases the quantum noise and artifacts in the acquired LDCT images. As a result, it produces visually low-quality LDCT images that adversely affect the disease diagnosing and treatment planning in clinical procedures. Deep Learning (DL) has recently become the cutting-edge technology of LDCT denoising due to its high performance and data-driven execution compared to conventional denoising approaches. Although the DL-based models perform fairly well in LDCT noise reduction, some noise components are still retained in denoised LDCT images. One reason for this noise retention is the direct transmission of feature maps through the skip connections of contraction and extraction path-based DL modes. Therefore, in this study, we propose a Generative Adversarial Network with Inception network modules (InNetGAN) as a solution for filtering the noise transmission through skip connections and preserving the texture and fine structure of LDCT images. The proposed Generator is modeled based on the U-net architecture. The skip connections in the U-net architecture are modified with three different inception network modules to filter out the noise in the feature maps passing over them. The quantitative and qualitative experimental results have shown the performance of the InNetGAN model in reducing noise and preserving the subtle structures and texture details in LDCT images compared to the other state-of-the-art denoising algorithms.
    Matched MeSH terms: Signal-To-Noise Ratio
  4. Fulltext Increasing iterative reconstruction strength at low tube voltage in coronary CT angiography protocols using 3D-printed and Catphan® 500 phantoms
    Abdullah KA, McEntee MF, Reed WM, Kench PL
    J Appl Clin Med Phys, 2020 Sep;21(9):209-214.
    PMID: 32657493 DOI: 10.1002/acm2.12977
    PURPOSE: The purpose of this study was to investigate the effect of increasing iterative reconstruction (IR) algorithm strength at different tube voltages in coronary computed tomography angiography (CCTA) protocols using a three-dimensional (3D)-printed and Catphan® 500 phantoms.

    METHODS: A 3D-printed cardiac insert and Catphan 500 phantoms were scanned using CCTA protocols at 120 and 100 kVp tube voltages. All CT acquisitions were reconstructed using filtered back projection (FBP) and Adaptive Statistical Iterative Reconstruction (ASIR) algorithm at 40% and 60% strengths. Image quality characteristics such as image noise, signal-noise ratio (SNR), contrast-noise ratio (CNR), high spatial resolution, and low contrast resolution were analyzed.

    RESULTS: There was no significant difference (P > 0.05) between 120 and 100 kVp measures for image noise for FBP vs ASIR 60% (16.6 ± 3.8 vs 16.7 ± 4.8), SNR of ASIR 40% vs ASIR 60% (27.3 ± 5.4 vs 26.4 ± 4.8), and CNR of FBP vs ASIR 40% (31.3 ± 3.9 vs 30.1 ± 4.3), respectively. Based on the Modulation Transfer Function (MTF) analysis, there was a minimal change of image quality for each tube voltage but increases when higher strengths of ASIR were used. The best measure of low contrast detectability was observed at ASIR 60% at 120 kVp.

    CONCLUSIONS: Changing the IR strength has yielded different image quality noise characteristics. In this study, the use of 100 kVp and ASIR 60% yielded comparable image quality noise characteristics to the standard CCTA protocols using 120 kVp of ASIR 40%. A combination of 3D-printed and Catphan® 500 phantoms could be used to perform CT dose optimization protocols.

    Matched MeSH terms: Signal-To-Noise Ratio
  5. Investigating the performance of an amplitude-independent algorithm for detecting the hand muscle activity of stroke survivors
    Hameed HK, Wan Hasan WZ, Shafie S, Ahmad SA, Jaafar H, Inche Mat LN
    J Med Eng Technol, 2020 Apr;44(3):139-148.
    PMID: 32396756 DOI: 10.1080/03091902.2020.1753838
    To make robotic hand devices controlled by surface electromyography (sEMG) signals feasible and practical tools for assisting patients with hand impairments, the problems that prevent these devices from being widely used have to be overcome. The most significant problem is the involuntary amplitude variation of the sEMG signals due to the movement of electrodes during forearm motion. Moreover, for patients who have had a stroke or another neurological disease, the muscle activity of the impaired hand is weak and has a low signal-to-noise ratio (SNR). Thus, muscle activity detection methods intended for controlling robotic hand devices should not depend mainly on the amplitude characteristics of the sEMG signal in the detection process, and they need to be more reliable for sEMG signals that have a low SNR. Since amplitude-independent muscle activity detection methods meet these requirements, this paper investigates the performance of such a method on people who have had a stroke in terms of the detection of weak muscle activity and resistance to false alarms caused by the involuntary amplitude variation of sEMG signals; these two parameters are very important for achieving the reliable control of robotic hand devices intended for people with disabilities. A comparison between the performance of an amplitude-independent muscle activity detection algorithm and three amplitude-dependent algorithms was conducted by using sEMG signals recorded from six hemiparesis stroke survivors and from six healthy subjects. The results showed that the amplitude-independent algorithm performed better in terms of detecting weak muscle activity and resisting false alarms.
    Matched MeSH terms: Signal-To-Noise Ratio
  6. Label-free optical spectroscopy for characterizing binding properties of highly sensitive nanocrystalline cellulose-graphene oxide based nanocomposite towards nickel ion
    Daniyal WMEMM, Fen YW, Abdullah J, Sadrolhosseini AR, Saleviter S, Omar NAS
    Spectrochim Acta A Mol Biomol Spectrosc, 2019 Apr 05;212:25-31.
    PMID: 30594850 DOI: 10.1016/j.saa.2018.12.031
    Surface plasmon resonance (SPR) is a label-free optical spectroscopy that is widely used for biomolecular interaction analysis. In this work, SPR was used to characterize the binding properties of highly sensitive nanocrystalline cellulose-graphene oxide based nanocomposite (CTA-NCC/GO) towards nickel ion. The formation of CTA-NCC/GO nanocomposite has been confirmed by FT-IR. The SPR analysis result shows that the CTA-NCC/GO has high binding affinity towards Ni2+ from 0.01 until 0.1 ppm with binding affinity constant of 1.620 × 103 M-1. The sensitivity for the CTA-NCC/GO calculated was 1.509° ppm-1. The full width at half maximum (FWHM), data accuracy (DA), and signal-to-noise ratio (SNR) have also been determined using the obtained SPR curve. For the FWHM, the value was 2.25° at 0.01 until 0.08 ppm and decreases to 2.12° at 0.1 until 10 ppm. The DA for the SPR curves is the highest at 0.01 until 0.08 ppm and lowest at 0.1 until 10 ppm. The SNR curves mirrors the curves of SPR angle shift where the SNR increases with the Ni2+ concentrations. For the selectivity test, the CTA-NCC/GO has the abilities to differentiate Ni2+ in the mixture of metal ions.
    Matched MeSH terms: Signal-To-Noise Ratio
  7. Fulltext Linguistic context effects in the speech perfection of Malay-speaking normal hearing young adults
    Cila Umat, Nahazatul Islia Jamari
    Jurnal Sains Kesihatan Malaysia, 2006;4(1):9-20.
    MyJurnal
    The study examined the use of linguistic contextual cues among native, Malay-speaking normal hearing young adults. Ten undergraduate students of Universiti Kebangsaan Malaysia participated in the study. All subjects had normal hearing with the average hearing threshold levels for the overall left and the right ears of 7.8 dB (SD 4.1). The Malay Hearing in Noise Test (MyHINT) materials were employed and presented to the subjects at an approximately 65 dBA presentation level. Testing was conducted in a sound field in three different listening conditions: in quiet, in noise with +5 dB signal-to-noise ratio (SNR) and 0 dB SNR. In every test condition, three lists of MyHINT were administered to each subject. The magnitude of context effects was measured using the j factor, which was derived from measurements of recognition probabilities for whole sentences (13,) and the constituent words in the sentences (PP) in which j = log P./ log P P. Results showed that all subjects scored 100% identification of words in sentences and whole sentences in quiet listening condition, while subjects' performances in 0 dB SNR were significantly poorer than that in quiet and in +5 dB SNR (p < 0.001). The j-values were significantly correlated with the probability of recognizing words in the sentences (r = 0.515, p = 0.029) in which lower j values were associated with lower P ps. Subjects were not significantly different from each other in their use of contextual cues in adverse listening conditions [F(9, 7) = 1.34, p = 0.359]. Using the linear regression function for j on word recognition probabilities, the predicted P. were calculated. It was found that the predicted and measured probabilities of recognizing whole sentences were highly correlated: r = 0.973, p < 0.001. The results suggested that linguistic contextual information become increasingly important for recognition of sentences by normal hearing young adult listeners as SNR deteriorates.
    Matched MeSH terms: Signal-To-Noise Ratio
  8. Fulltext Machine learning techniques for diabetic macular edema (DME) classification on SD-OCT images
    Alsaih K, Lemaitre G, Rastgoo M, Massich J, Sidibé D, Meriaudeau F
    Biomed Eng Online, 2017 Jun 07;16(1):68.
    PMID: 28592309 DOI: 10.1186/s12938-017-0352-9
    BACKGROUND: Spectral domain optical coherence tomography (OCT) (SD-OCT) is most widely imaging equipment used in ophthalmology to detect diabetic macular edema (DME). Indeed, it offers an accurate visualization of the morphology of the retina as well as the retina layers.

    METHODS: The dataset used in this study has been acquired by the Singapore Eye Research Institute (SERI), using CIRRUS TM (Carl Zeiss Meditec, Inc., Dublin, CA, USA) SD-OCT device. The dataset consists of 32 OCT volumes (16 DME and 16 normal cases). Each volume contains 128 B-scans with resolution of 1024 px × 512 px, resulting in more than 3800 images being processed. All SD-OCT volumes are read and assessed by trained graders and identified as normal or DME cases based on evaluation of retinal thickening, hard exudates, intraretinal cystoid space formation, and subretinal fluid. Within the DME sub-set, a large number of lesions has been selected to create a rather complete and diverse DME dataset. This paper presents an automatic classification framework for SD-OCT volumes in order to identify DME versus normal volumes. In this regard, a generic pipeline including pre-processing, feature detection, feature representation, and classification was investigated. More precisely, extraction of histogram of oriented gradients and local binary pattern (LBP) features within a multiresolution approach is used as well as principal component analysis (PCA) and bag of words (BoW) representations.

    RESULTS AND CONCLUSION: Besides comparing individual and combined features, different representation approaches and different classifiers are evaluated. The best results are obtained for LBP[Formula: see text] vectors while represented and classified using PCA and a linear-support vector machine (SVM), leading to a sensitivity(SE) and specificity (SP) of 87.5 and 87.5%, respectively.

    Matched MeSH terms: Signal-To-Noise Ratio
  9. Fulltext Modified algorithm for image watermarking using 2D-DCT and Elgamal Cryptosyst
    Nur Azien Yazid, Kamilah Abdullah, Suhaila Abd Halim
    ESTEEM Academic Journal, 2019;15(1):44-55.
    MyJurnal
    Image watermarking embeds identifying information in an image in such a manner that it cannot easily be removed. For the past several years, image digital watermarking has become a necessary element used for hiding secret image and enabling secured communication such as
    privacy, confidentiality, authentication and data integrity. Although numerous watermarking schemes are present in grayscale images, the present work focuses on the RGB color image. This study proposed a new hybrid method that would satisfy the essential needs of modern image watermarking. The color image watermarking is based on the 2D Discrete Cosine Transform and Elgamal cryptosystem. The 2D Discrete Cosine Transform depends on the matrix products, while the Elgamal cryptosystem depends on the discrete logarithm problem. The cryptosystem is combined with existing Arnold transform in watermarking algorithm to enhance the security of secret image. Value of Peak Signal to Noise Ratio was taken as performance evaluation parameters. On the whole, the performance evaluation shows that combining the two algorithms improved the performance of image watermarking.
    Matched MeSH terms: Signal-To-Noise Ratio
  10. Fulltext Morphological techniques for microcalcification and mass enhancement
    Nor'aida Khairuddin, Norriza Mohd Isa, Wan Muhamad Saridan Wan Hassan
    Journal of Nuclear and Related Technologies, 2012;2012(2):102-108.
    MyJurnal
    The recognition of microcalcifications and masses from digital mammographic images are important to aid the detection of breast cancer. In this paper, we applied morphological techniques to extract the embedded structures from the images for subsequent analysis. A mammographic phantom was created with embedded structures such as micronodules, nodules and fibrils. For the preprocessing techniques, intensity transformation of gray scale was applied to the image. The structures of the image were enhanced and segmented using dilation for a morphological operation with morphological closing. Next, low pass Gaussian filter was applied to the image to smooth and reduce noises. It was found that our method improved the detection of microcalcifications and masses with high Peak Signal To Noise Ratio (PSNR).
    Matched MeSH terms: Signal-To-Noise Ratio
  11. Fulltext Multi-frequency ultrasound imaging: phantom study
    Siti Nur Masturah Abdul Malek, Sayed Inayatullah Shah
    International Journal of Allied Health Sciences, 2018;2(2):304-309.
    MyJurnal
    In ultrasound imaging there is compromise between the penetration of signal at certain depths into the object and image resolution as the ultrasound probe only can transmit single frequency signals in one transmission. Using curvilinear ultrasound probe with 2 to 5 MHz frequency bandwidth, this study investigated the use of multi-frequency imaging to enhance the quality of phantom images.
    Methods: Siemen Acuson X150 with curvilinear ultrasound transducer was used to scan the organs of interest (kidney, gallbladder and pancreas) of the ultrasound abdominal phantom. Different images at the different selected frequencies (2.5, 3.6 and 5.0 MHz) were created by fixing the position and the orientation of the transducer in each of the scanning process. Different-frequency images were generated and combined to produce composite (multi-frequency) image. Results: In this study, the quality of the composite image was evaluated based on signal-to noise ratio (SNR) and the obtained results were compared with the single frequency images. Besides, the comparison was also made in terms of overall image quality (noise and sharpness of organ outline) through perceived image quality analysis. Based on calculated SNR, the composite image of the kidney, gallbladder and pancreas recorded higher SNR value as compared to the single frequency images. However, through perceived image quality, most of the observers viewed that the quality of the composite image of the kidney, gallbladder and pancreas is poor as compared to the single frequency image. Conclusions: Image quality of ultrasound imaging is improved by combining multiple ultrasound frequency images into a single composite image. This is achieved as high SNR is obtained in the composite image. However, through perceived image quality, the overall image quality of the composite image was poor.
    Matched MeSH terms: Signal-To-Noise Ratio
  12. Fulltext Multi-level basis selection of wavelet packet decomposition tree for heart sound classification
    Safara F, Doraisamy S, Azman A, Jantan A, Abdullah Ramaiah AR
    Comput Biol Med, 2013 Oct;43(10):1407-14.
    PMID: 24034732 DOI: 10.1016/j.compbiomed.2013.06.016
    Wavelet packet transform decomposes a signal into a set of orthonormal bases (nodes) and provides opportunities to select an appropriate set of these bases for feature extraction. In this paper, multi-level basis selection (MLBS) is proposed to preserve the most informative bases of a wavelet packet decomposition tree through removing less informative bases by applying three exclusion criteria: frequency range, noise frequency, and energy threshold. MLBS achieved an accuracy of 97.56% for classifying normal heart sound, aortic stenosis, mitral regurgitation, and aortic regurgitation. MLBS is a promising basis selection to be suggested for signals with a small range of frequencies.
    Matched MeSH terms: Signal-To-Noise Ratio
  13. Noise variance estimation using image noise cross-correlation model on SEM images
    Sim KS, Nia ME, Tso CP
    Scanning, 2013 May-Jun;35(3):205-12.
    PMID: 22961698 DOI: 10.1002/sca.21055
    A number of techniques have been proposed during the last three decades for noise variance and signal-to-noise ratio (SNR) estimation in digital images. While some methods have shown reliability and accuracy in SNR and noise variance estimations, other methods are dependent on the nature of the images and perform well on a limited number of image types. In this article, we prove the accuracy and the efficiency of the image noise cross-correlation estimation model, vs. other existing estimators, when applied to different types of scanning electron microscope images.
    Matched MeSH terms: Signal-To-Noise Ratio
  14. On optimizing the blocking step of indirect enzyme-linked immunosorbent assay for Epstein-Barr virus serology
    Lim CS, Krishnan G, Sam CK, Ng CC
    Clin Chim Acta, 2013 Jan 16;415:158-61.
    PMID: 23043757 DOI: 10.1016/j.cca.2012.08.031
    Because blocking agent occupies most binding surface of a solid phase, its ability to prevent nonspecific binding determines the signal-to-noise ratio (SNR) and reliability of an enzyme-linked immunosorbent assay (ELISA).
    Matched MeSH terms: Signal-To-Noise Ratio
  15. Optimization of dose and image quality of paediatric cardiac catheterization procedure
    Lubis LE, Bayuadi I, Pawiro SA, Ng KH, Bosmans H, Soejoko DS
    Phys Med, 2015 Nov;31(7):659-68.
    PMID: 26050060 DOI: 10.1016/j.ejmp.2015.05.011
    The purpose of this study is to quantify the quality of the available imaging modes for various iodine-based contrast agent concentration in paediatric cardiology. The figure of merit (FOM) was defined as the squared signal to noise ratio divided by a patient dose related parameter. An in house constructed phantom simulated a series of vessel segments with iodine concentrations from 10% or 30 mg/cc to 16% or 48 mg/cc of iodine in a blood plasma solution, all within the dimensional constraints of a paediatric patient. The phantom also used test inserts of tin (Sn). Measurements of Entrance Surface Air Kerma (ESAK) and exit dose rate were performed along with calculations of the signal-to-noise ratio (SNR) of all the objects. A first result showed that it was favourable to employ low dose fluoroscopy mode and lower frame rate modes in cine acquisition if dynamic information is not critical. Normal fluoroscopy dose mode provided a considerably higher dose level (in comparison to low dose mode) with only a slight improvement in SNR. Higher frame rate cine modes should be used however when the clinical situation dictates so. This work also found that tin should not be intended as iodine replacement material for research purposes due to the mismatching SNR, particularly on small vessel sizes.
    Matched MeSH terms: Signal-To-Noise Ratio
  16. Overcoming Limitations of LoRa Physical Layer in Image Transmission
    Jebril AH, Sali A, Ismail A, Rasid MFA
    Sensors (Basel), 2018 Sep 27;18(10).
    PMID: 30262793 DOI: 10.3390/s18103257
    As a possible implementation of a low-power wide-area network (LPWAN), Long Range (LoRa) technology is considered to be the future wireless communication standard for the Internet of Things (IoT) as it offers competitive features, such as a long communication range, low cost, and reduced power consumption, which make it an optimum alternative to the current wireless sensor networks and conventional cellular technologies. However, the limited bandwidth available for physical layer modulation in LoRa makes it unsuitable for high bit rate data transfer from devices like image sensors. In this paper, we propose a new method for mangrove forest monitoring in Malaysia, wherein we transfer image sensor data over the LoRa physical layer (PHY) in a node-to-node network model. In implementing this method, we produce a novel scheme for overcoming the bandwidth limitation of LoRa. With this scheme the images, which requires high data rate to transfer, collected by the sensor are encrypted as hexadecimal data and then split into packets for transfer via the LoRa physical layer (PHY). To assess the quality of images transferred using this scheme, we measured the packet loss rate, peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) index of each image. These measurements verify the proposed scheme for image transmission, and support the industrial and academic trend which promotes LoRa as the future solution for IoT infrastructure.
    Matched MeSH terms: Signal-To-Noise Ratio
  17. Fulltext Performance of ultra-wideband systems in the presence of WiFi and 3G signals
    Rashid, A.S., Khatun, S., Ali, B.M., Khazani, A.M.
    ASM Science Journal, 2008;2(1):13-22.
    MyJurnal
    An analysis of the power spectral density of ultra-wideband (UWB) signals is presented in order to evaluate the effects of cumulative interference from multiple UWB devices on victim narrowband systems in their overlay bands like WiFi (i.e. IEEE802.11a) and 3rdG systems (Universal mobile telecommunications system/wideband code division multiple access). In this paper, the performances are studied through the bit-error-rate as a function of signal-to-noise ratio as well as signal-to-interference power ratio using computer simulation and exploiting the realistic channel model (i.e. modified Saleh-Valenzuela model). Several modifications of a generic Gaussian pulse waveform with lengths in the order of nanoseconds were used to generate UWB spectra. Different kinds of pulse modulation (i.e. antipodal and orthogonal) schemes were also taken into account.
    Matched MeSH terms: Signal-To-Noise Ratio
  18. Fulltext Quantitative assessment on coronary computed tomography angiography (CCTA) image quality: comparisons between genders and different tube voltage settings
    Chian TC, Nassir NM, Ibrahim MI, Yusof AK, Sabarudin A
    Quant Imaging Med Surg, 2017 Feb;7(1):48-58.
    PMID: 28275559 DOI: 10.21037/qims.2017.02.02
    BACKGROUND: This study was carried out to quantify and compare the quantitative image quality of coronary computed tomography angiography (CCTA) between genders as well as between different tube voltages scan protocols.

    METHODS: Fifty-five cases of CCTA were collected retrospectively and all images including reformatted axial images at systolic and diastolic phases as well as images with curved multi planar reformation (cMPR) were obtained. Quantitative image quality including signal intensity, image noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of right coronary artery (RCA), left anterior descending artery (LAD), left circumflex artery (LCx) and left main artery (LM) were quantified using Analyze 12.0 software.

    RESULTS: Six hundred and fifty-seven coronary arteries were evaluated. There were no significant differences in any quantitative image quality parameters between genders. 100 kilovoltage peak (kVp) scanning protocol produced images with significantly higher signal intensity compared to 120 kVp scanning protocol (P<0.001) in all coronary arteries in all types of images. Higher SNR was also observed in 100 kVp scan protocol in all coronary arteries except in LCx where 120 kVp showed better SNR than 100 kVp.

    CONCLUSIONS: There were no significant differences in image quality of CCTA between genders and different tube voltages. Lower tube voltage (100 kVp) scanning protocol is recommended in clinical practice to reduce the radiation dose to patient.

    Matched MeSH terms: Signal-To-Noise Ratio
  19. Fulltext Receiver diversity combining using evolutionary algorithms in Rayleigh fading channel
    Akbari M, Manesh MR, El-Saleh AA, Reza AW
    ScientificWorldJournal, 2014;2014:128195.
    PMID: 25045725 DOI: 10.1155/2014/128195
    In diversity combining at the receiver, the output signal-to-noise ratio (SNR) is often maximized by using the maximal ratio combining (MRC) provided that the channel is perfectly estimated at the receiver. However, channel estimation is rarely perfect in practice, which results in deteriorating the system performance. In this paper, an imperialistic competitive algorithm (ICA) is proposed and compared with two other evolutionary based algorithms, namely, particle swarm optimization (PSO) and genetic algorithm (GA), for diversity combining of signals travelling across the imperfect channels. The proposed algorithm adjusts the combiner weights of the received signal components in such a way that maximizes the SNR and minimizes the bit error rate (BER). The results indicate that the proposed method eliminates the need of channel estimation and can outperform the conventional diversity combining methods.
    Matched MeSH terms: Signal-To-Noise Ratio
  20. Reducing charging effects in scanning electron microscope images by Rayleigh contrast stretching method (RCS)
    Wan Ismail WZ, Sim KS, Tso CP, Ting HY
    Scanning, 2011 Jul-Aug;33(4):233-51.
    PMID: 21611953 DOI: 10.1002/sca.20237
    To reduce undesirable charging effects in scanning electron microscope images, Rayleigh contrast stretching is developed and employed. First, re-scaling is performed on the input image histograms with Rayleigh algorithm. Then, contrast stretching or contrast adjustment is implemented to improve the images while reducing the contrast charging artifacts. This technique has been compared to some existing histogram equalization (HE) extension techniques: recursive sub-image HE, contrast stretching dynamic HE, multipeak HE and recursive mean separate HE. Other post processing methods, such as wavelet approach, spatial filtering, and exponential contrast stretching, are compared as well. Overall, the proposed method produces better image compensation in reducing charging artifacts.
    Matched MeSH terms: Signal-To-Noise Ratio
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