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.
Breaking Degradation Coupling: A Structural Entropy Guided Decoupled Framework and Benchmark for Infrared Enhancement
Faculty of Information Engineering and Automation, Kunming University of Science and Technology(昆明理工大学信息工程与自动化学院);Department of Biomedical Engineering, Hefei University of Technology(合肥工业大学生物医学工程系);School of Mathematics and Statistics, Yunnan University(云南大学数学与统计学院)
Enhancing Infrared Vision: Progressive Prompt Fusion Network and Benchmark
School of Software Engineering, Dalian University of Technology(大连理工大学软件学院);Information Science and Technology College, Dalian Martime University(大连海事大学信息科学与技术学院)
Abstract PURPOSES this study aims to perform microcalsification detection by performing image enhancement in mammography image by using transformation of negative image and histogram equalization. image mammography with .pgm format changed to. jpg format then processed into negative image result then processed again using histogram equalization. the results of the image enhancement process using negative image techniques and equalization histograms are compared and validated with MSE and PSNR on each mammographic image. CONCLUSION: Image enhancement process on mammography image can be done, ho…
Multifarious image enhancement algorithms have been used in different applications. Still, some algorithms or modules are imperfect for practical use. When the image enhancement modules have been fixed or combined by a series of algorithms, we need to repair them as a whole part without changing the inside. This report aims to find an algorithm based on trained filters to repair low-quality image enhancement modules. A brief review on basic image enhancement techniques and pixel classification methods will be presented, and the procedure of trained filters will be described step by step. The e…
There are several images that do not have uniform brightness which pose a challenging problem for image enhancement systems. As histogram equalization has been successfully used to correct for uniform brightness problems, a histogram equalization method that utilizes human visual system based thresholding(human vision thresholding) as well as logarithmic processing techniques were introduced later . But these methods are not good for preserving the local content of the image which is a major factor for various images like medical and aerial images. Therefore new method is proposed here. This m…
University College of Engineering, Punjabi University(旁遮普大学工程学院)
Principle objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a multitude of choices for improving the visual quality of images. Appropriate choice of such techniques is greatly influenced by the imaging modality, task at hand and viewing conditions. This paper will provide an overview of underlying concepts, along with algorithms commonly used for image enhancement. The paper focuses on spatial domain techniques for image enhancement, with particular reference to point …
Unified Restoration-Perception Learning: Maritime Infrared-Visible Image Fusion and Segmentation
Laboratory of Underwater Acoustic Communication and Marine Information Technology, Ministry of Education, Xiamen University(厦门大学水声通信与海洋信息技术教育部重点实验室);PAMI Research Group, Department of Computer and Information Science, University of Macau(澳门大学计算机与信息科学系PAMI研究组);School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University(中山大学深圳校区网络空间安全学院)
Image enhancement using the visible (V) and near-infrared (NIR) usually enhances useful image details. The enhanced images are evaluated by observers perception, instead of quantitative feature evaluation. Thus, can we say that these enhanced images using NIR information has better features in comparison to the computed features in the Red, Green, and Blue color channels directly? In this work, we present a new method to enhance the visible images using NIR information via edge-preserving filters, and also investigate which method performs best from a image features standpoint. We then show th…
Histogram Equalization is a contrast enhancement technique in the image processing which uses the histogram of image. However histogram equalization is not the best method for contrast enhancement because the mean brightness of the output image is significantly different from the input image. There are several extensions of histogram equalization has been proposed to overcome the brightness preservation challenge. Contrast enhancement using brightness preserving bi-histogram equalization (BBHE) and Dualistic sub image histogram equalization (DSIHE) which divides the image histogram into two pa…
University of Moratuwa(莫勒图沃大学);Base Hospital Kebithigollawa(科比蒂戈勒沃基地医院)
The morphology of blood vessels in retinal fundus images is an important indicator of diseases like glaucoma, hypertension and diabetic retinopathy. The accuracy of retinal blood vessels segmentation affects the quality of retinal image analysis which is used in diagnosis methods in modern ophthalmology. Contrast enhancement is one of the crucial steps in any of retinal blood vessel segmentation approaches. The reliability of the segmentation depends on the consistency of the contrast over the image. This paper presents an assessment of the suitability of a recently invented spatially adaptive…
Infrared and Visible Image Fusion with Hierarchical Human Perception
School of Electronic Engineering, Xidian University(西安电子科技大学电子工程学院);Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications(重庆邮电大学图像认知重点实验室)
Indian Institute of Technology Indore(印度理工学院印多尔分校)
Fingerprint recognition techniques are immensely dependent on quality of the fingerprint images. To improve the performance of recognition algorithm for poor quality images an efficient enhancement algorithm should be designed. Performance improvement of recognition algorithm will be more if enhancement process is adaptive to the fingerprint quality (wet, dry or normal). In this paper, a quality adaptive fingerprint enhancement algorithm is proposed. The proposed fingerprint quality assessment algorithm clusters the fingerprint images in appropriate quality class of dry, wet, normal dry, norma…
Silicon photodiode based CMOS sensors with backside-illumination for 300 to 1000 nm wavelength range were studied. We showed that a single hole in the photodiode increases the optical efficiency of the pixel. In near-infrared wavelengths, the enhancement allows 70% absorption in a 3 microns thick Si. It is 4x better than for the flat pixel. We compared different shapes and sizes of single holes and holes arrays. We have shown that a certain size and shape in single holes pronounce better optical efficiency enhancement. The crosstalk was successfully reduced with trenches between pixels. We opt…
This paper developed a brightness enhancement technique for video frame pixel intensity improvement. Frames extracted from the six sample video data used in this work were stored in the form of images in a buffer. Noise was added to the extracted image frames to vary the intensity of their pixels so that the pixel values of the noisy images differ from their true values in order to determine the efficiency of the developed technique. Simulation results showed that, the developed technique was efficient with an improved pixel intensity and histogram distribution. The Peak to Signal Noise Ratio …
Deep learning techniques are applied so as to increase the spatial resolution of Sentinel2 satellite imagery, depicting the Amynteo lignite mine in Ptolemaida, Greece. Resolution enhancement by factors 2 and 4 as well as by factors 2 and 6 using Very-Deep SuperResolution (VDSR) and DSen2 networks, respectively, provides fairly well results on Amynteo lignite mine images.