The authors describe a new algorithm for the fast Hough transform (FHT) that satisfactorily solves the problems other fast algorithms propose in the literature-erroneous solutions, point redundance, scaling, and detection of straight lines of different sizes-and needs less storage space. By using the information generated by the algorithm for the detection of straight lines, they manage to detect the segments of the image without appreciable computational overhead. They also discuss the performance and the parallelization of the algorithm and show its efficiency with some examples.

Coordinate Rotation DIgital Computer (CORDIC) rotator is a well known and widely used algorithm within computers due to its way of carrying out some calculations such as trigonometric functions, among others. A scale factor compensation inherent to the CORDIC algorithm becomes an important drawback when trying to improve its benefits, although some authors have come up with a new scaling-free version, which has been successfully implemented within wireless applications. However, this new CORDIC can still be significantly improved by modifying some of its parts, therefore, this paper shows an enhanced version of the scaling-free CORDIC. These new enhancements have been implemented and tested, obtaining some new architectures which are able to reach a 35% lower latency and a 36% reduction in area and power consumption compared to the original scaling-free architecture.

The unfolded and pipelined CORDIC is a high-performance hardware element that produces a wide variety of one and two argument functions with high throughput. The reduction in delay, power, and area (cost) are of significant interest regarding this module due to its high demand for resources. The linear approximation to rotation has been proposed to achieve such reductions. However, the schemes for rotation (multiplication) and vectoring (division) complicate the implementation in a single unit. In this work, we improve the linear approximation scheme, leading to a unified implementation for rotation and vectoring, where fully parallel tree multipliers are used instead of the second half of CORDIC iterations. We also combine the linear approximation to rotation with the scale factor compensation so that the compensation is concurrently performed with the rotation process. We then extend the method to 3D CORDIC. Such an extension is not straightforward due to the lack of existing analytical expressions for the convergence of the algorithm. A comparison, using a rough area-time model and synthesis results, shows that our proposals may achieve significant reductions in delay, with no increase in area, in actual implementations.

Although redundant addition is widely used to design parallel multioperand adders for ASIC implementations, the use of redundant adders on Field Programmable Gate Arrays (FPGAs) has generally been avoided. The main reasons are the efficient implementation of carry propagate adders (CPAs) on these devices (due to their specialized carry-chain resources) as well as the area overhead of the redundant adders when they are implemented on FPGAs. This paper presents different approaches to the efficient implementation of generic carry-save compressor trees on FPGAs. They present a fast critical path, independent of bit width, with practically no area overhead compared to CPA trees. Along with the classic carry-save compressor tree, we present a novel linear array structure, which efficiently uses the fast carry-chain resources. This approach is defined in a parameterizable HDL code based on CPAs, which makes it compatible with any FPGA family or vendor. A detailed study is provided for a wide range of bit widths and large number of operands. Compared to binary and ternary CPA trees, speedups of up to 2.29 and 2.14 are achieved for 16-bit width and up to 3.81 and 3.11 for 64-bit width.