جهت دسترسی به کاربرگه ی زیر، از این لینک استفاده کنید. http://dl.pgu.ac.ir/handle/Hannan/56494
Title: Recurrently decomposable 2-D convolvers for FPGA-based digital image processing
Keywords: Science & Technology;Technology;Engineering, Electrical & Electronic;Engineering;Field-programmable gate arrays (FPGAs);large convolution mask;recurrently decomposable (RD);two-dimensional (2-D) convolution;REAL-TIME COMPUTATION;ARCHITECTURE;CONVOLUTION;Electrical & Electronic Engineering; Electrical And Electronic Engineering
Issue Date: 29-Feb-2016
17-Jan-2016
Publisher: IEEE
Description: Two-dimensional (2-D) convolution is a widely used operation in image processing and computer vision, characterized by intensive computation and frequent memory accesses. Previous efforts to improve the performance of field-programmable gate array (FPGA) convolvers focused on the design of buffering schemes and on minimizing the use of multipliers. A recently proposed recurrently decomposable (RD) filter design method can reduce the computational complexity of 2-D convolutions by splitting the convolution between an image and a large mask into a sequence of convolutions using several smaller masks. This brief explores how to efficiently implement RD based 2-D convolvers using FPGA. Three FPGA architectures are proposed based on RD filters, each with a different buffering scheme. The conclusion is that RD based architectures achieve higher area efficiency than other previously reported state-of-the-art methods, especially for larger convolution masks. An area efficiency metric is also suggested, which allows the most appropriate architecture to be selected.
Other Identifiers: 1549-7747
http://hdl.handle.net/10044/1/33197
Type Of Material: Other
Appears in Collections:Bioengineering

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