IR image databases generation under target intrinsic thermal variability constraints

TL;DR

This paper presents a novel method for generating realistic infrared image databases with intrinsic thermal variability, crucial for ATR evaluation, by superimposing targets on backgrounds under quality constraints and modeling target signatures with 3D textures.

Contribution

It introduces a new approach to create diverse, realistic IR images with thermal variability using superimposition and 3D modeling techniques.

Findings

Generated IR databases meet quality constraints.

Realistic thermal variability achieved through 3D textured models.

Enhanced ATR assessment with diverse IR datasets.

Abstract

This paper deals with the problem of infrared image database generation for ATR assessment purposes. Huge databases are required to have quantitative and objective performance evaluations. We propose a method which superimpose targets and occultants on background under image quality metrics constraints to generate realistic images. We also propose a method to generate target signatures with intrinsic thermal variability based on 3D models plated with real infrared textures.