An Improved TLLCM Infrared Small Target Detection Method Based on Difference of Gaussians

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Small target detection has great theoretical significance in the field of infrared (IR). Local contrast measure (LCM) has shown commendable performance in infrared small target detection. However, existing LCM methodologies primarily emphasize the background suppression rate, which leads to a decline in detection accuracy. In this paper, an enhanced algorithm based on the framework of Tri-layer LCM(TLLCM) is introduced, which incorporates the Difference of Gaussians (DoG) algorithm and morphological filtering operations. The proposed algorithm demonstrates an improvement in both Precision and Recall metrics, while preserving the low false alarm rate advantage inherent to TLLCM. On dataset IRSTD-1k, proposed method achieves BSF of 1934.61, SCRG of 27.74, Precision rate of 0.52 and Recall rate of 0.64.

Original languageEnglish
Title of host publicationProceedings of the 44th Chinese Control Conference, CCC 2025
EditorsJian Sun, Hongpeng Yin
PublisherIEEE Computer Society
Pages7552-7557
Number of pages6
ISBN (Electronic)9789887581611
DOIs
Publication statusPublished - 2025
Externally publishedYes
Event44th Chinese Control Conference, CCC 2025 - Chongqing, China
Duration: 28 Jul 202530 Jul 2025

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference44th Chinese Control Conference, CCC 2025
Country/TerritoryChina
CityChongqing
Period28/07/2530/07/25

Keywords

  • Difference Of Gaussians
  • Infrared Small-Target Detection
  • Local Contrast Measure
  • Morphological Filtering
  • Tri-layer Window

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