
Validation of the FPGA-Based Image Processing Techniques using the efficient tool like Xilinx Device Generators
Publication year - 2021
Publication title -
international journal of emerging trends in engineering research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.218
H-Index - 14
ISSN - 2347-3983
DOI - 10.30534/ijeter/2021/16942021
Subject(s) - field programmable gate array , computer science , image processing , generator (circuit theory) , digital image processing , process (computing) , grayscale , matlab , artificial intelligence , image (mathematics) , image fusion , computer hardware , computer vision , embedded system , power (physics) , physics , quantum mechanics , operating system
Foremost Image Enhancement's intent is to analyze an image in a direction that the output becomes more appropriate for a particular application, rather than the original picture. Image enhancement methods include a multitude of options for enhancing the image accuracy of photographs. The appropriate choice of such strategies is strongly determined by the imaging modality. FPGA has several main features that can be used as a tool for the processing of authentic time algorithms. It gives significantly higher efficiency over the programmable processor. This paper presents information regarding FPGA implementation of Image Processing Algorithms using Xilinx System Generator (XSG). Xilinx Application Generator is a Xilinx existing application process that makes FPGA hardware design relatively easy. For synthesis and simulation, the Xilinx device generator is initiated with MATLAB. To reintroduce a wide range of image processing algorithms, a model-based analysis approach will be used. Various classification algorithms for RGB to grayscale, image negativity, image retrieval, contrast stretching, threshold, boundaries extraction, as well as various image fusion methods are explored, and therefore how they are implemented using available Device Generator components