Novel robust optimal filter design method and new transition band analysis

Author(s):  
Hsiao-Chun Wu
2011 ◽  
Vol 57 (4) ◽  
pp. 465-472 ◽  
Author(s):  
Maciej Sac ◽  
Marek Blok

A Nearly Optimal Fractional Delay Filter Design Using an Asymmetric WindowIn this paper a numerically efficient filter design method suitable for variable fractional delay (VFD) filter implementation is investigated. We propose to use a well known window method with an asymmetric window extracted from optimal filter designed beforehand. As we will demonstrate, such an approach, if additional gain correction is applied, allows for nearly optimal VFD filter design. Thus, the proposed approach combines window method simplicity with performance comparable to that of optimal filters. Efficiency of the presented technique makes it suitable for designing filters with varying delay in real time.


2013 ◽  
Vol 756-759 ◽  
pp. 3831-3834 ◽  
Author(s):  
Yu Long Ying ◽  
Dan Er Chen

This paper investigates the problem of automated defect detection for textile fabrics and proposes a new optimal filter design method for solving this problem. Wavelet is used to extract the texture features of textile fabrics. In view of this optimal filter, a news semi-supervised segmentation algorithm is then proposed. The performance of the scheme is evaluated by using a variety of homogeneous textile images with different types of common defects. The test results exhibit accurate defect detection with low false alarm, thus confirming the robustness and effectiveness of the proposed scheme.


2003 ◽  
Vol 39 (8) ◽  
pp. 695 ◽  
Author(s):  
G. Jovanovic-Dolecek ◽  
J. Diaz-Carmona

2011 ◽  
Vol 128-129 ◽  
pp. 181-184
Author(s):  
You Lian Zhu ◽  
Cheng Huang

Design of morphological filter greatly depends on morphological operations and structuring elements selection. A filter design method used median closing morphological operation is proposed to enhance the image denoising ability and the PSO algorithm is introduced for structural elements selecting. The method takes the peak value signal-to-noise ratio (PSNR) as the cost function and may adaptively build unit structuring elements with zero square matrix. Experimental results show the proposed method can effectively remove impulse noise from a noisy image, especially from a low signal-to-noise ratio (SNR) image; the noise reduction performance has obvious advantages than the other.


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