Dynamic optimization of hessian determinant image pyramid for memory‐efficient and high performance keypoint detection in SURF

Matching of keypoints across image patches forms the basis of computer vision applications, such as object detection, recognition, and tracking in real-world images. Most of keypoint methods are mainly used to match the high-resolution images, which always utilize an image pyramid for multiscale keypoint detection. In this paper, we propose a novel keypoint method to improve the matching performance of image patches with the low-resolution and small size. The location, scale, and orientation of keypoints are directly estimated from an original image patch using a Log-Spiral sampling pattern for keypoint detection without consideration of image pyramid. A Log-Spiral sampling pattern for keypoint description and two bit-generated functions are designed for generating a binary descriptor. Extensive experiments show that the proposed method is more effective and robust than existing binary-based methods for image patch matching.

Download Full-text

A High-Performance and Memory-Efficient Pipeline Architecture for the 5/3 and 9/7 Discrete wavelet Transform of JPEG2000 Codec

IEEE Transactions on Circuits and Systems for Video Technology ◽

10.1109/tcsvt.2005.856898 ◽

2005 ◽

pp. 1-1

Author(s):

Bing-Fei Wu ◽

Chung-Fu Lin

Keyword(s):

Wavelet Transform ◽

Discrete Wavelet Transform ◽

High Performance ◽

Discrete Wavelet ◽

Pipeline Architecture ◽

Memory Efficient

Download Full-text

A High Performance and Memory Efficient LU Decomposer on FPGAs

IEEE Transactions on Computers ◽

10.1109/tc.2010.278 ◽

2012 ◽

Vol 61 (3) ◽

pp. 366-378 ◽

Cited By ~ 21

Author(s):

Guiming Wu ◽

Yong Dou ◽

Junqing Sun ◽

Gregory D. Peterson

Keyword(s):

High Performance ◽

Memory Efficient

Download Full-text

Efficient ancestry and mutation simulation with msprime 1.0

Genetics ◽

10.1093/genetics/iyab229 ◽

2021 ◽

Author(s):

Franz Baumdicker ◽

Gertjan Bisschop ◽

Daniel Goldstein ◽

Graham Gower ◽

Aaron P Ragsdale ◽

...

Keyword(s):

Population Genetics ◽

Data Structure ◽

Software Quality ◽

High Performance ◽

Sequence Data ◽

Ground Truth ◽

Development Model ◽

Ground Truth Data ◽

Open Source Development ◽

Memory Efficient

Abstract Stochastic simulation is a key tool in population genetics, since the models involved are often analytically intractable and simulation is usually the only way of obtaining ground-truth data to evaluate inferences. Because of this, a large number of specialized simulation programs have been developed, each filling a particular niche, but with largely overlapping functionality and a substantial duplication of effort. Here, we introduce msprime version 1.0, which efficiently implements ancestry and mutation simulations based on the succinct tree sequence data structure and the tskit library. We summarize msprime’s many features, and show that its performance is excellent, often many times faster and more memory efficient than specialized alternatives. These high-performance features have been thoroughly tested and validated, and built using a collaborative, open source development model, which reduces duplication of effort and promotes software quality via community engagement.

Download Full-text

VLSI Implementation of a High-Performance Nonlinear Image Scaling Algorithm

Journal of Healthcare Engineering ◽

10.1155/2021/6297856 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Osamah Ibrahim Khalaf ◽

Carlos Andrés Tavera Romero ◽

A. Azhagu Jaisudhan Pazhani ◽

G. Vinuja

Keyword(s):

High Performance ◽

Low Cost ◽

Vlsi Architecture ◽

Linear Interpolation ◽

Noisy Environments ◽

Image Scaling ◽

Scaling Methods ◽

Processing Resources ◽

Weighted Median ◽

Memory Efficient

This study implements the VLSI architecture for nonlinear-based picture scaling that is minimal in complexity and memory efficient. Image scaling is used to increase or decrease the size of an image in order to map the resolution of different devices, particularly cameras and printers. Larger memory and greater power are also necessary to produce high-resolution photographs. As a result, the goal of this project is to create a memory-efficient low-power image scaling methodology based on the effective weighted median interpolation methodology. Prefiltering is employed in linear interpolation scaling methods to improve the visual quality of the scaled image in noisy environments. By decreasing the blurring effect, the prefilter performs smoothing and sharpening processes to produce high-quality scaled images. Despite the fact that prefiltering requires more processing resources, the suggested solution scales via effective weighted median interpolation, which reduces noise intrinsically. As a result, a low-cost VLSI architecture can be created. The results of simulations reveal that the effective weighted median interpolation outperforms other existing approaches.

Download Full-text