V. S. Dimitrov

D. F. G. Coelho, R. J. Cintra, A. C. Frery et al.

This paper introduces a fast algorithm for simultaneous inversion and determinant computation of small sized matrices in the context of fully Polarimetric Synthetic Aperture Radar (PolSAR) image processing and analysis. The proposed fast algorithm is based on the computation of the adjoint matrix and the symmetry of the input matrix. The algorithm is implemented in a general purpose graphical processing unit (GPGPU) and compared to the usual approach based on Cholesky factorization. The assessment with simulated observations and data from an actual PolSAR sensor show a speedup factor of about two when compared to the usual Cholesky factorization. Moreover, the expressions provided here can be implemented in any platform.

R. J. Cintra, V. S. Dimitrov

In this paper, we introduce a new class of transform method --- the arithmetic cosine transform (ACT). We provide the central mathematical properties of the ACT, necessary in designing efficient and accurate implementations of the new transform method. The key mathematical tools used in the paper come from analytic number theory, in particular the properties of the Riemann zeta function. Additionally, we demonstrate that an exact signal interpolation is achievable for any block-length. Approximate calculations were also considered. The numerical examples provided show the potential of the ACT for various digital signal processing applications.

D. F. G. Coelho, R. J. Cintra, F. M. Bayer et al.

This paper introduced a matrix parametrization method based on the Loeffler discrete cosine transform (DCT) algorithm. As a result, a new class of eight-point DCT approximations was proposed, capable of unifying the mathematical formalism of several eight-point DCT approximations archived in the literature. Pareto-efficient DCT approximations are obtained through multicriteria optimization, where computational complexity, proximity, and coding performance are considered. Efficient approximations and their scaled 16- and 32-point versions are embedded into image and video encoders, including a JPEG-like codec and H.264/AVC and H.265/HEVC standards. Results are compared to the unmodified standard codecs. Efficient approximations are mapped and implemented on a Xilinx VLX240T FPGA and evaluated for area, speed, and power consumption.

J. Adikari, V. S. Dimitrov, R. J. Cintra

Koblitz curves are a special set of elliptic curves and have improved performance in computing scalar multiplication in elliptic curve cryptography due to the Frobenius endomorphism. Double-base number system approach for Frobenius expansion has improved the performance in single scalar multiplication. In this paper, we present a new algorithm to generate a sparse and joint $τ$-adic representation for a pair of scalars and its application in double scalar multiplication. The new algorithm is inspired from double-base number system. We achieve 12% improvement in speed against state-of-the-art $τ$-adic joint sparse form.

N. Rajapaksha, A. Madanayake, R. J. Cintra et al.

The discrete cosine transform (DCT) is a widely-used and important signal processing tool employed in a plethora of applications. Typical fast algorithms for nearly-exact computation of DCT require floating point arithmetic, are multiplier intensive, and accumulate round-off errors. Recently proposed fast algorithm arithmetic cosine transform (ACT) calculates the DCT exactly using only additions and integer constant multiplications, with very low area complexity, for null mean input sequences. The ACT can also be computed non-exactly for any input sequence, with low area complexity and low power consumption, utilizing the novel architecture described. However, as a trade-off, the ACT algorithm requires 10 non-uniformly sampled data points to calculate the 8-point DCT. This requirement can easily be satisfied for applications dealing with spatial signals such as image sensors and biomedical sensor arrays, by placing sensor elements in a non-uniform grid. In this work, a hardware architecture for the computation of the null mean ACT is proposed, followed by a novel architectures that extend the ACT for non-null mean signals. All circuits are physically implemented and tested using the Xilinx XC6VLX240T FPGA device and synthesized for 45 nm TSMC standard-cell library for performance assessment.

A. Edirisuriya, A. Madanayake, R. J. Cintra et al.

An area efficient row-parallel architecture is proposed for the real-time implementation of bivariate algebraic integer (AI) encoded 2-D discrete cosine transform (DCT) for image and video processing. The proposed architecture computes 8$\times$8 2-D DCT transform based on the Arai DCT algorithm. An improved fast algorithm for AI based 1-D DCT computation is proposed along with a single channel 2-D DCT architecture. The design improves on the 4-channel AI DCT architecture that was published recently by reducing the number of integer channels to one and the number of 8-point 1-D DCT cores from 5 down to 2. The architecture offers exact computation of 8$\times$8 blocks of the 2-D DCT coefficients up to the FRS, which converts the coefficients from the AI representation to fixed-point format using the method of expansion factors. Prototype circuits corresponding to FRS blocks based on two expansion factors are realized, tested, and verified on FPGA-chip, using a Xilinx Virtex-6 XC6VLX240T device. Post place-and-route results show a 20% reduction in terms of area compared to the 2-D DCT architecture requiring five 1-D AI cores. The area-time and area-time${}^2$ complexity metrics are also reduced by 23% and 22% respectively for designs with 8-bit input word length. The digital realizations are simulated up to place and route for ASICs using 45 nm CMOS standard cells. The maximum estimated clock rate is 951 MHz for the CMOS realizations indicating 7.608$\cdot$10$^9$ pixels/seconds and a 8$\times$8 block rate of 118.875 MHz.

R. J. Cintra, V. S. Dimitrov, H. M. de Oliveira et al.

Fragile digital watermarking has been applied for authentication and alteration detection in images. Utilizing the cosine and Hartley transforms over finite fields, a new transform domain fragile watermarking scheme is introduced. A watermark is embedded into a host image via a blockwise application of two-dimensional finite field cosine or Hartley transforms. Additionally, the considered finite field transforms are adjusted to be number theoretic transforms, appropriate for error-free calculation. The employed technique can provide invisible fragile watermarking for authentication systems with tamper location capability. It is shown that the choice of the finite field characteristic is pivotal to obtain perceptually invisible watermarked images. It is also shown that the generated watermarked images can be used as publicly available signature data for authentication purposes.