2d fir filters
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This paper proposes an analytical design procedure for a particular class of 2D filters, namelyGaussian-shaped, circularly-symmetric FIR filters. We approach both low-pass and band-pass circular filters,which are adjustable in selectivity and peak frequency. The design starts from a given 1D Gaussian prototypefilter, approximated using the Chebyshev series. A frequency transformation is applied to derive the circularfilter. Several design examples are provided for both types of filters. The filters designed through this methodare efficient, their frequency response results in a factored or nested form, convenient for implementation.


2016 ◽  
Vol 35 (6) ◽  
pp. 2213-2257 ◽  
Author(s):  
Apoorva Aggarwal ◽  
Manjeet Kumar ◽  
Tarun Kumar Rawat ◽  
Dharmendra Kumar Upadhyay

2014 ◽  
Vol 651-653 ◽  
pp. 2116-2120
Author(s):  
Yun Long Wang ◽  
Shi Hu Wang

In the aid of sinc sum function and matrix equation a new 2D window function is obtained. It is as simple as a 2D cosine window function. Comparison shows that the new 2D window function can provide much better 2D FIR filters than 2D Hamming window function. Maximum passband ripples are about 2.5-3.5 times smaller and maximum stopband ripples are about 1.5 times smaller with equal or very small different passband and stopband edge frequencies.


VLSI Design ◽  
2014 ◽  
Vol 2014 ◽  
pp. 1-24 ◽  
Author(s):  
Daniel Llamocca ◽  
Marios Pattichis

We introduce a dynamically reconfigurable 2D filterbank that supports both real and complex-valued inputs, outputs, and filter coefficients. This general purpose filterbank allows for the efficient implementation of 2D filterbanks based on separable 2D FIR filters that support all possible combinations of input and output signals. The system relies on the use of dynamic reconfiguration of real/complex one-dimensional filters to minimize the required hardware resources. The system is demonstrated using an equiripple and a Gabor filterbank and the results using both real and complex-valued input images. We summarize the performance of the system in terms of the required processing times, energy, and accuracy.


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