Adaptive FPGA NoC-based Architecture for Multispectral Image Correlation
Linlin Zhang (LAHC), Anne Claire Legrand (LAHC), Virginie Fresse, (LAHC), Viktor Fischer (LAHC)

TL;DR
This paper presents an adaptive FPGA-based NoC architecture designed for multispectral image correlation, comparing various distance algorithms to optimize performance based on complexity, precision, and execution time.
Contribution
It introduces a flexible FPGA NoC architecture that supports multiple distance algorithms for multispectral image analysis, with a comparative evaluation of their performance.
Findings
RGB algorithm implementation discussed
Comparison of distance algorithms based on complexity and precision
Adaptive architecture enhances multispectral image correlation
Abstract
An adaptive FPGA architecture based on the NoC (Network-on-Chip) approach is used for the multispectral image correlation. This architecture must contain several distance algorithms depending on the characteristics of spectral images and the precision of the authentication. The analysis of distance algorithms is required which bases on the algorithmic complexity, result precision, execution time and the adaptability of the implementation. This paper presents the comparison of these distance computation algorithms on one spectral database. The result of a RGB algorithm implementation was discussed.
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Taxonomy
TopicsCCD and CMOS Imaging Sensors · Advanced Data Compression Techniques · Digital Image Processing Techniques
