A Novel Speech Compression Technique Using Optimized Wavelet Transform to Improve the Quality of Auditory Perception Under Low SNR Conditions

2019 ◽  
Author(s):  
V Vijayasri Bolisetty ◽  
Santi Prabha
Keyword(s):  
Wavelet Transform ◽  
Auditory Perception ◽  
Speech Compression ◽  
Compression Technique ◽  
Low Snr

scholarly journals Speech Enhancement Based on the Multi-Scales and Multi-Thresholds of the Auditory Perception Wavelet Transform

2011 ◽  
Vol 36 (3) ◽  
pp. 519-532 ◽  
Author(s):  
Zhi Tao ◽  
He-Ming Zhao ◽  
Xiao-Jun Zhang ◽  
Di Wu
Keyword(s):  
Wavelet Transform ◽  
Speech Enhancement ◽  
Auditory Perception ◽  
Noise Suppression ◽  
Signal To Noise Ratio ◽  
Masking Effect ◽  
Auditory Masking ◽  
Low Snr ◽  
Residual Noise ◽  
Multi Scales

Abstract This paper proposes a speech enhancement method using the multi-scales and multi-thresholds of the auditory perception wavelet transform, which is suitable for a low SNR (signal to noise ratio) environment. This method achieves the goal of noise reduction according to the threshold processing of the human ear's auditory masking effect on the auditory perception wavelet transform parameters of a speech signal. At the same time, in order to prevent high frequency loss during the process of noise suppression, we first make a voicing decision based on the speech signals. Afterwards, we process the unvoiced sound segment and the voiced sound segment according to the different thresholds and different judgments. Lastly, we perform objective and subjective tests on the enhanced speech. The results show that, compared to other spectral subtractions, our method keeps the components of unvoiced sound intact, while it suppresses the residual noise and the background noise. Thus, the enhanced speech has better clarity and intelligibility.

scholarly journals Edge Preserved Image Compression Technique Using Wavelet and Edge Based Segmentation

2012 ◽  
pp. 180-185
Author(s):  
A.Benjamin Joseph ◽  
Dr. R. Baskaran
Keyword(s):  
Wavelet Transform ◽  
Compression Ratio ◽  
Low Frequency ◽  
Haar Wavelet ◽  
Compression Technique ◽  
Edge Preserving ◽  
Haar Wavelet Transform ◽  
Bit Plane ◽  
Edge Based

This paper presents a new approach of edge preserving and edge based segmentation for compression of images using Modified Fast Haar wavelet transform (MFHW) and Bit Plane Encoder to elevate the compression ratio with high picture quality. The edges of an image are preserved to increase the PSNR, and then the detected edges are used to segment the foreground and background images. The Foreground of the image is given more importance than the background images. A wavelet transform is used to extract the redundant information at low frequency and a matching Bit Plane encoder is used to code the segments of the image at different quality levels. The Proposed method highly preserves quality of the foreground image. Normal compression algorithms will not preserve the high frequency details such as edges, corners etc., in this method edges are preserved and used for segmenting the layers of the original image. The two level Fast haar Wavelet transform is used to decompose the image at different frequency levels, which has high multi-resolution characteristics. The proposed method increases both the compression ratio and PSNR.

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 An innovative image fusion algorithm based on wavelet transform and discrete fast curvelet transform

2011 ◽  
Vol 1 (3) ◽  
Author(s):  
T. Sumathi ◽  
M. Hemalatha
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Curvelet Transform ◽  
Relevant Information ◽  
Good Time ◽  
Discrete Wavelet ◽  
Fusion Algorithm ◽  
Time Frequency ◽  
Fused Image

AbstractImage fusion is the method of combining relevant information from two or more images into a single image resulting in an image that is more informative than the initial inputs. Methods for fusion include discrete wavelet transform, Laplacian pyramid based transform, curvelet based transform etc. These methods demonstrate the best performance in spatial and spectral quality of the fused image compared to other spatial methods of fusion. In particular, wavelet transform has good time-frequency characteristics. However, this characteristic cannot be extended easily to two or more dimensions with separable wavelet experiencing limited directivity when spanning a one-dimensional wavelet. This paper introduces the second generation curvelet transform and uses it to fuse images together. This method is compared against the others previously described to show that useful information can be extracted from source and fused images resulting in the production of fused images which offer clear, detailed information.

Processing of Sonar Image Based on Compressive Sensing

2011 ◽  
Vol 301-303 ◽  
pp. 719-723 ◽  
Author(s):  
Zhi Jing Xu ◽  
Huan Lei Dai ◽  
Pei Pei Cao
Keyword(s):  
Wavelet Transform ◽  
Matching Pursuit ◽  
Experimental Result ◽  
Underwater Acoustic Channel ◽  
Sonar Image ◽  
Underwater Image ◽  
Reconstruction Image ◽  
Observation Matrix ◽  
Efficient Transmission

The particularity of the underwater acoustic channel has put forward a higher request for collection and efficient transmission of the underwater image. In this paper, based on the characteristics of sonar image, wavelet transform is used to sparse decompose the image, and selecting Gaussian random matrix as the observation matrix and using the orthogonal matching pursuit (OMP) algorithm to reconstruct the image. The experimental result shows that the quality of the reconstruction image and PSNR have gained great ascension compared to the traditional compression and processing of image based on the wavelet transform while they have the same measurement numbers in the coding portion. It provides a convenient for the sonar image’s underwater transmission.

DAUBECHIES COMPLEX WAVELET TRANSFORM BASED TECHNIQUE FOR DENOISING OF MEDICAL IMAGES

2007 ◽  
Vol 07 (04) ◽  
pp. 663-687 ◽  
Author(s):  
ASHISH KHARE ◽  
UMA SHANKER TIWARY
Keyword(s):  
Wavelet Transform ◽  
Image Denoising ◽  
Medical Image ◽  
Medical Images ◽  
Universal Method ◽  
Complex Wavelet Transform ◽  
Shrinkage Function ◽  
Daubechies Complex Wavelet Transform ◽  
Complex Wavelet

Wavelet based denoising is an effective way to improve the quality of images. Various methods have been proposed for denoising using real-valued wavelet transform. Complex valued wavelets exist but are rarely used. The complex wavelet transform provides phase information and it is shift invariant in nature. In medical image denoising, both removal of phase incoherency as well as maintaining the phase coherency are needed. This paper is an attempt to explore and apply the complex Daubechies wavelet transform for medical image denoising. We have proposed a method to compute a complex threshold, which does not depend on any assumed model of noise. In this sense this is a "universal" method. The proposed complex-domain shrinkage function depends on mean, variance and median of wavelet coefficients. To test the effectiveness of the proposed method, we have computed the input and output SNR and PSNR of various types of medical images. The method gives an improvement for Gaussian additive, Speckle and Salt-&-Pepper noise as well as for the mixture of these noise types for a range of noisy images with 15 db to 30 db noise levels and outperforms other real-valued wavelet transform based methods. The application of the proposed method to Ultrasound, X-ray and MRI images is demonstrated in the experiments.

scholarly journals Deep Learning-Based Wavelet Threshold Function Optimization on Noise Reduction in Ultrasound Images

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Zhuxiang Shen ◽  
Wei Li ◽  
Hui Han
Keyword(s):  
Wavelet Transform ◽  
Image Denoising ◽  
Similarity Index ◽  
Speckle Noise ◽  
Disease Diagnosis ◽  
Function Optimization ◽  
Threshold Function ◽  
Ultrasound Images ◽  
Better Than

To explore the utilization of the convolutional neural network (CNN) and wavelet transform in ultrasonic image denoising and the influence of the optimized wavelet threshold function (WTF) algorithm on image denoising, in this exploration, first, the imaging principle of ultrasound images is studied. Due to the limitation of the principle of ultrasound imaging, the inherent speckle noise will seriously affect the quality of ultrasound images. The denoising principle of the WTF based on the wavelet transform is analyzed. Based on the traditional threshold function algorithm, the optimized WTF algorithm is proposed and applied to the simulation experiment of ultrasound images. By comparing quantitatively and qualitatively with the traditional threshold function algorithm, the advantages of the optimized WTF algorithm are analyzed. The results suggest that the image is denoised by the optimized WTF. The mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measurement (SSIM) of the images are 20.796 dB, 34.294 dB, and 0.672 dB, respectively. The denoising effect is better than the traditional threshold function. It can denoise the image to the maximum extent without losing the image information. In addition, in this exploration, the optimized function is applied to the actual medical image processing, and the ultrasound images of arteries and kidneys are denoised separately. It is found that the quality of the denoised image is better than that of the original image, and the extraction of effective information is more accurate. In summary, the optimized WTF algorithm can not only remove a lot of noise but also obtain better visual effect. It has important value in assisting doctors in disease diagnosis, so it can be widely applied in clinics.

scholarly journals Fusion of Medical Images in Wavelet Domain: A Discrete Mathematical Model

2018 ◽  
Vol 14 (25) ◽  
pp. 1-11
Author(s):  
Satya Prakash Yadav ◽  
Sachin Yadav
Keyword(s):  
Wavelet Transform ◽  
Image Compression ◽  
Image Fusion ◽  
Data Transfer ◽  
Discrete Wavelet ◽  
Related Information ◽  
Medical Domain ◽  
Discrete Mathematical Model ◽  
Treatment Procedures

Introduction: Image compression is a great instance for operations in the medical domain that leads to better understanding and implementations of treatment, especially in radiology. Discrete wavelet transform (dwt) is used for better and faster implementation of this kind of image fusion.Methodology: To access the great feature of mathematical implementations in the medical domain we use wavelet transform with dwt for image fusion and extraction of features through images.Results: The predicted or expected outcome must help better understanding of any kind of image resolutions and try to compress or fuse the images to decrease the size but not the pixel quality of the image.Conclusions: Implementation of the dwt mathematical approach will help researchers or practitioners in the medical domain to attain better implementation of the image fusion and data transmission, which leads to better treatment procedures and also decreases the data transfer rate as the size will be decreased and data loss will also be manageable.Originality: The idea of using images may decrease the size of the image, which may be useful for reducing bandwidth while transmitting the images. But the thing here is to maintain the same quality while transmitting data and also while compressing the images.Limitations: As this is a new implementation, if we have committed any mistakes in image compression of medical-related information, this may lead to treatment faults for the patient. Image quality must not be reduced with this implementation.

scholarly journals Sensory Marketing in the Quality of Service of the Hotel El Libertador in the City of Riobamba

2021 ◽  
Author(s):  
Diana Carolina García Mayorga ◽  
Jorge Antonio Vasco Vasco ◽  
Juan Carlos Montufar Guevara
Keyword(s):  
Quality Of Service ◽  
Visual Perception ◽  
Service Quality ◽  
Auditory Perception ◽  
Marketing Strategies ◽  
Existing Problems ◽  
Sensory Marketing ◽  
Palabras Clave ◽  
The City

This research aimed to improve the perception of the quality of service of the Hotel El Libertador by means of sensory marketing elements to improve the tourist experience. The study variables were derived from the visual, auditory and kinesthetic perceptions related to the quality of service. In addition, an analysis was performed with the EEG MindWave Mobile 2 biometric equipment, to understand the levels of attention, meditation and blinking. In terms of visual perception, it was determined that attention should be paid to the clothing of the staff (27.6%) and signage (40.9%). The elements of the auditory perception of the hotel had low ratings because the hotel has not implemented elements of auditory sensory marketing in the facilities. Four of the seven elements of the kinesthetic perceptions were not attended and had a weight between 38.3% and 46.7%. As a result of these analyses, a sensory marketing proposal was suggested, which included visual, auditory and kinesthetic marketing strategies, to provide a solution to the existing problems with the hotel facilities. Based on the biometric equipment results, a proposal was made for sensory marketing strategies with elements of experiential communication to be used in the hotel’s facilities which would also improve the perception of service quality. Keywords: sensory marketing, perception, tourism, senses, quality of service, neuromarketing. Resumen La investigación tuvo como objetivo mejorar la percepción en la calidad de servicio del HOTEL EL LIBERTADOR, por medio de elementos de marketing sensorial mejorando la experiencia del turista. La investigación es de tipo correlacional, las variables de estudio se desprenden de la percepción visual, auditiva y kinestésica relacionada con la variable calidad del servicio, además se realizó un análisis con equipo biométrico EEG MindWave Mobile 2 en las instalaciones de la empresa para identificar los niveles de atención, meditación y parpadeo. En los elementos de percepción visual se determinó que se debe prestar atención a la vestimenta del personal que tiene un 27,6% y la señalética 40,9%. Los elementos de la percepción auditiva del hotel tienen una baja calificación porque el hotel no ha implementado elementos de marketing sensorial auditivo en las instalaciones, 4 de los 7 elementos de la percepción kinestésica no han sido atendidos y tienen una ponderación entre 38,3% a 46,7% Por medio de este análisis se planteó una propuesta de marketing sensorial para dar solución a la problemática existente en las instalaciones del hotel, la misma que contiene estrategias de marketing visual, auditivo y kinestésico. Mediante la obtención de resultados y análisis realizados con equipos biométricos, se pudo determinar estrategias de marketing sensorial con elementos de comunicación experiencial en las instalaciones de la empresa hotelera que permita mejorar la percepción de la calidad de servicio. Palabras clave: marketing sensorial, percepción, turísmo, sentidos, calidad de servicio, neuromarketing.

Sign in / Sign up

Export Citation Format

Share Document