Co-designed platform proposal for remote sensing images processing

• Grant number: 16/04553-2
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: February 01, 2017
• End date: January 31, 2018
• Field of knowledge: Physical Sciences and Mathematics - Geosciences
• Principal Investigator: Erivaldo Antonio da Silva
• Grantee: Guilherme Pina Cardim
• Supervisor: Ignacio Bravo Muñoz
• Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
• Institution abroad: Universidad de Alcalá (UAH), Spain
• Associated to the scholarship: 14/24392-8 - Proposal of co-design platform for processing remote sensing images, BP.DR

Abstract

The digital image processing (DIP) consists of an area of great interest in studies, which usually requires a large amount of information processing. In Cartography, the DIP is widely used in remote sensing studies to detect interest features in the images. Nowadays, with great technological advances, the remote sensing images have high spatial resolution with large amount of information to be processed during the studies developed using these images. Therefore, the processing of high spatial resolution images needs high time to complete all the processing. For that reason, several libraries of digital image processing have emerged in the literature to facilitate the use and improve the performance of the DIP functions, such as OpenCV, DipImage and CARTOMORPH. Among the mentioned libraries, it is worth mentioning the importance of the CARTOMORPH library for the Cartography area, since it was developed to studies of cartographic feature detection and it is focused on mathematical morphology techniques, which are highlighting in related studies. However, sometimes the processing of cartographic images of high resolution, using DIP libraries, is still slow because of the large amount of information to be processed and the complexity of some DIP algorithms. Therefore, the current project proposes a methodology to analyze routines of cartographic features detection, developed with the CARTOMORPH library, split them and control the flow of operations. After the routine division, the proposal continues with the possibility of sending part of the processing to a hardware platform, which will be defined during the project development and will be responsible for the processing that requires high computational cost. This way, there is a proposal for a co-designed system combining hardware and software for processing of high resolution images, from remote sensors, for achievement of expected results in a shorter processing time. The project is justified by the need of studies to enhance the performance and reduce the waiting time of researchers, in the Cartography area, developing computational routines to detect cartographic features in remote sensing images. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CARDIM, GUILHERME PINA; DA SILVA, ERIVALDO ANTONIO; DIAS, MAURICIO ARAUJO; BRAVO, IGNACIO; GARDEL, ALFREDO. A nonrecursive GR algorithm to extract road networks in high-resolution images from remote sensing. EARTH SCIENCE INFORMATICS, AUG 2020. (16/04553-2, 14/24392-8)

PINA CARDIM, GUILHERME; DA SILVA, ERIVALDO ANTONIO; DIAS, MAURICIO ARAUJO; BRAVO, IGNACIO; GARDEL, ALFREDO. Statistical Evaluation and Analysis of Road Extraction Methodologies Using a Unique Dataset from Remote Sensing. REMOTE SENSING, v. 10, n. 4, APR 2018. (16/04553-2, 14/24392-8)

CARDIM, GUILHERME PINA; DA SILVA, ERIVALDO ANTONIO; DIAS, MAURICIO ARAUJO; BRAVO, IGNACIO; GARDEL, ALFREDO. A nonrecursive GR algorithm to extract road networks in high-resolution images from remote sensing. EARTH SCIENCE INFORMATICS, v. 13, n. 4, p. 13-pg., 2020-08-13. (14/24392-8, 16/04553-2)