Performance Evaluation of Infrared Image Enhancement Techniques
원문 초록
Infrared (IR) images are widely used in many fields such as medical imaging, object tracking, astronomy and military purposes for securing borders. Infrared images can be captured day or night based on the type of capturing device. The capturing devices use electromagnetic radiation with longer wavelengths. There are several types of IR radiation based on the range of wavelength and corresponding frequency. Due to noising and other artifacts, IR images are not clearly visible. In this paper, we present a complete up-todate survey on IR imaging enhancement techniques. The survey includes IR radiation types and devices and existing IR datasets. The survey covers spatial enhancement techniques, frequency-domain based enhancement techniques and Deep learning-based techniques.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
SonarT165: A Large-scale Benchmark and STFTrack Framework for Acoustic Object Tracking
Statistical Machine Learning for Astronomy -- A Textbook
HiM2SAM: Enhancing SAM2 with Hierarchical Motion Estimation and Memory Optimization towards Long-term Tracking
HVI-CIDNet+: Beyond Extreme Darkness for Low-Light Image Enhancement
A Survey on Prompt Tuning
A Survey on Latent Reasoning
토론
이 논문과 연결된 포럼 글이 아직 없습니다.