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This study addresses the blind image deconvolution which uses only blurred image and less point spread function (PSF) information to restore the original image. To identify the blind image it is a very important step for restoring the image. Therefore, the first step is to look for PSF model. In this paper, particle swarm optimization (PSO) is utilized to seek the unknown PSF. The objective function...
Noise reduction has a lot attention no matter in practical applications or a signal processing research field. Recently, a novel denoisy method which removes noise from received signals by threshold operation on wavelet coefficients was developed and its efficiency has been confirmed. However, its definition of parameters is not general-purpose enough to deal with variant cases. In order to seek high...
Recently, the research which based on wavelet representation to reduce noise has gotten a lot of attention. The most typical method, universal threshold proposed by Donoho, and its derivative methods have verified their efficiency on varied applications. Some settings which are signal-dependence are critical; however, they were usually given by trial and error or a rough estimate in existing algorithms...
For the research field of adaptive de-noisy, the technique which determinates an adequate threshold in wavelet domain of signal is novel and feasible. The most of threshold determination are developed from universal method proposed by Donoho. Unfortunately, these methods are just performed in some wavelet level and involve several incorrectly estimated factors; therefore, they can't result the best...
Noise reduction problem is addressed by this study. Recently, wavelet thresholding has become popular and has gotten much attention among a number of de-noisy approaches. The most of threshold determination are developed from universal method proposed by Donoho. But, some shortcomings of the determination are caused from several incorrectly estimated factors and the lack of adaptability for whole...
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