TY  - BOOK
AU  - Zhu,Hu
AU  - Pan,Yushan
AU  - Deng,Lizhen
AU  - Xu,Guoxia
ED  - SpringerLink (Online service)
TI  - Infrared Small Target Detection: Theory, Methods, and Algorithms. 
SN  - 9789819997992
AV  - TA1501-1820 
PY  - 2024///
CY  - Singapore
PB  - Springer Nature Singapore, Imprint: Springer
KW  - Image processing
KW  - Digital techniques
KW  - Computer vision
KW  - Artificial intelligence
KW  - Computer science
KW  - Mathematics
KW  - Software engineering
KW  - Programming languages (Electronic computers)
KW  - Computer Imaging, Vision, Pattern Recognition and Graphics
KW  - Artificial Intelligence
KW  - Mathematics of Computing
KW  - Theory of Computation
KW  - Software Engineering
KW  - Programming Language
N1  - Chapter 1: Introduction -- Chapter 2: Preliminaries.-Chapter 3: Morphological Transformation for infrared small object detection -- Chapter 4: Low-rank tensor decomposition for infrared small object detection -- Chapter 5: Deep learning methods for infrared small object detection -- Chapter 6: Performance of different methods. Chapter 7: Summary and Outlook of research on infrared small target detection
N2  - Uncover the secrets of cutting-edge research in “Infrared Small Target Detection,” a crucial resource that delves into the dynamic world of infrared imaging and detection algorithms. This comprehensive book is an indispensable gem for the research community, offering a profound introduction to the theory, methods, and algorithms underlying infrared small object detection. As an invaluable guide, this book explores diverse models and categories of infrared small object detection algorithms, providing meticulous descriptions and comparisons of their strengths and limitations. Perfectly tailored for researchers, practitioners, and students with a passion for infrared imaging and detection, this book equips readers with the necessary knowledge to embark on groundbreaking investigations in this field.Readers can particularly be drawn to the book's methods, results, and topics, encompassing diverse categories of infrared small object detection algorithms and their corresponding advantages and disadvantages. The book also imparts foundational knowledge in mathematical morphology, tensor decomposition, and deep learning, enabling readers to grasp the underlying principles of these advanced algorithms. Experience the key benefits of “Infrared Small Target Detection” as readers gain a profound understanding of theory, methods, and algorithms tailored to infrared small object detection. The comprehensive descriptions and comparisons of various algorithm categories empower readers to select the perfect algorithms for their specific applications. Unlock the potential of this groundbreaking resource with a basic understanding of mathematics, statistics, and image processing. Some familiarity with infrared imaging and detection proves advantageous in fully immersing oneself in the wealth of knowledge presented within these pages
UR  - https://doi.org/10.1007/978-981-99-9799-2
ER  -