A Self-Reconfigurable Platform for the Implementation of 2D Filterbanks with Real and Complex-Valued Inputs, Outputs, and Filter Coefficients

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. 1. Introduction Filterbank implementations in hardware require significant resources. Each filter in the filterbank is often implemented using multiply-and-add circuitry (modifiable coefficients) or by a fixed-coefficient circuitry. In what follows, we will use the term static implementations to describe filterbank implementations that are based on fixed hardware. A clear limitation of static implementations comes from the fact that hardware resources cannot be adjusted based on the number of coefficients or the number of filters. Furthermore, energy consumption is often a function of the implemented static hardware regardless of whether the hardware resources are actually used. Dynamic partial reconfiguration (DPR) technology is becoming increasingly popular for addressing the aforementioned problems by time-multiplexing FPGA resources [1]. For filterbanks, DPR lets us implement only one filter at a time, which can potentially result in significant power savings over static implementation approaches. In this paper, we introduce a self-reconfigurable implementation for a 2D complex filterbank that only requires one 1D filter to be present on the FPGA at a time. We study all the possible cases as well as providing results in terms of accuracy, energy, and performance. Applications of complex filterbanks can be found in [2, 3]. For efficient hardware realizations, we focus on 2D FIR separable filtering that allows implementations by means of two 1D FIR filters. This separability property allows us to consider a DPR approach that keeps only one filter (row or column) at a time. We presented some related earlier work in [4–7]. In [4], we described an efficient 1D FIR filtering system that combined the distributed arithmetic (DA) technique with DPR. An early 2D real filterbank implementation was presented in [5]. We presented a dynamic real 2D FIR filter