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2nd International Conference on Circuits, Controls, and Communications (CCUBE)

作者： Mondal, Milton Joshi, S. D. Indian Inst Technol Dept Elect Engn Delhi India

ISBN: (纸本)9781538606155

Super Resolution (SR) algorithm produces a high resolution (HR) image from single or multiple low resolution (LR) images. This algorithm is used to overcome the limitation of imaging CMOS sensors. It is difficult to obtain a HR image by reducing the size of the sensor after a certain limit. SR technique is used in many visual applications like biological imaging, military applications and forensic investigations. It is basically an inexpensive process to enhance the resolution of an image and to extract the high-frequency information. Two different adaptive schemes are proposed here. First one focuses on minimizing the error between the actual image and the estimated image. Resolution enhancement is done here by simultaneously modeling a blurring filter to capture the degradation process as well as modeling an innovation filter to remove the blurring effects, sensor noise using adaptive Least Square technique. The second scheme incorporates the advantages of both visual quality improvement as well as the increase in PSNR by jointly using wavelet transforms and adaptive normalized Least Mean Square (NLMS) technique. Results and performances of these novel techniques are compared with other available Super Resolution methods in terms of the visual quality index like PSNR, SSIM. Numerical results indicate that these computationally efficient single image super resolution techniques are very effective in real life imaging applications as a significant improvement of visual quality is observed in the super resolved image.

关键词： sub-band coder Discrete wavelet transform (DWT) Normalized Least Mean Square (NLMS) Technique Single Image Super Resolution (SISR) Structural Similarity (SSIM) Redundant Wavelet Transform (RWT)

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A COMPARATIVE PERFORMANCE EVALUATION OF PITCH ESTIMATION METHODS FOR TDHS/sub-band CODING OF SPEECH

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SPEECH COMMUNICATION 1984年第3期3卷 253-259页

作者： PALIWAL, KK AARSKOG, AI UNIV TRONDHEIM ELECTR RES LAB TRONDHEIM NORWAY

The time-domain harmonic-scaling (TDHS) algorithm provides a computationally efficient method (suitable for real-time implementation) for speech bandwith compression and expansion. Pitch estimation is an important operation in the TDHS process. In the present paper, we study a TDHS/sub-band coding system for speech operating at 16 kbits/s and investigate the relative effectiveness of five different pitch estimation methods (the autocorrelation method, the cepstrum method, the simplified inverse filtering technique, the average magnitude difference function method and the maximum likelihood method). A formal listening test using 17 human listeners is conducted for their comparative performance evaluation. The average magnitude difference function method was found to be the best pitch estimation method for TDHS/sub-band coding. Der Algorithms zur TDHS-Zeitkompression (Time-Domain Harmonic Scaling) stelt ein numerisch leistungsfähiges Verfahren zur bandbreitenkompression und -dehnung dar (er kann in Echtzeit implementiert werden). Die Bestimmung der Grundfrequenz ist eine wichtige Etappe innerhalb des TDHS-Verfahrens. In diesem Beitrag untersuchen ir ein TDHS-Teilbandkodierungsyustem, welches mit 16 kbits/s arbeitet, und vergleichen die Liestungsfähigkeit von fünf Grundfrequenzbestimmungsmethoden (Autokorrelationsmethode, Ceptrummethode, SIFT-Methode, AMDF-Methode, Methode der “Maximum Likelihood”). Ein psychoakustischer Test mit 17 Hörern erlaubt den Vergleich der Leistungsfähigkeit der verschiedenen Methoden. Die AMDF-Methode erwies sich als am besten geeignetes Verfahren im Rahmen eines TDHS-Teilbandkodierungssystems. L'algorithme de transformation d'échelle de fréquence dans le domaine temporel (TDHS) fournit une méthode numériquement efficace (appropriée à une implantation en temps réel) pour la compression et l'expansion de la largeur de la bande fréuentielle de la parole. L'estimation du pitch représente une opération importante de la procédure TDHS. Dans cet ar

关键词： Speech coding TDHS algorithm sub-band coder pitch estimation

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