Enhancement of infrared (IR) images is a perplexing task. Infrared imaging finds its applications in military and defense related problems. Since IR devices capture only the heat emitting objects, the visualization of the IR images is very poor. To improve the quality of the given IR image for better perception, suitable enhancement routines are required such that contrast can be improved that suits well for human visual system. To accomplish the task, a fuzzy set based enhancement of IR images is proposed in this paper. The proposed method is adaptive in nature since the required parameters are calculated based on the image characteristics. Experiments are carried out on standard benchmark database and the results show the efficacy of the proposed method. © Springer-Verlag Berlin Heidelberg 2015.

Rajkumar S

Department of Information Security

School of Computer Science and Engineering

Vellore Campus

Soundrapandiyan R

Chandra Mouli P.V.S.S.R.

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Perceptual Visualization Enhancement of Infrared Images Using Fuzzy Sets

Transactions on Computational Science XXV Lecture Notes in Computer Science

Image enhancement is the process of modifying digital images so that results are suitable for human perception. An upcoming need for image visualization during all lighting conditions by the use of infrared (IR) imagery has gained momentum. It is deemed fit for efficient target acquisition and object deduction. However, due to low image resolution and difficulty in spotting certain objects whose temperature is similar to that of the ground, infrared images must be subjected to further enhancement. Our given proposal aims to enhance infrared images, making use of the fuzzy-based enhancement technique (FBE), and to compare its efficacy with other techniques such as histogram equalization (HE), adaptive histogram equalization (AHE), max–median filter, and multi-scale top-hat transform. The enhanced image is then analyzed using different quantitative metrics such as peak signal-to-noise ratio (PSNR), image quality index (IQI), and structural similarity (SSIM) for performance evaluation. From experimental results, it is concluded that FBE results in the best quality image. © Springer Nature Singapore Pte Ltd. 2018.

Advances in Intelligent Systems and Computing Speech and Language Processing for Human-Machine Communications

Adaptive Infrared Images Enhancement Using Fuzzy-Based Concepts

The contrast enhancement, brightness preserving and natural look of the output image plays an important role in an infrared (IR) image enhancement process. There are several IR image enhancement algorithms that have been developed, but they may produce artificial looking images, and the images derived from these methods are not suitable for applications such as surveillance, environmental monitoring and so on. In this paper, an algorithm using new top-hat transform and multi-scale sequential toggle operator has been proposed. Firstly, a new white top-hat transform and new black top-hat transform is generated to extract the light and dark regions of the image. Then, the multi-scale sequential toggle operator is used on the extracted light and dark regions to get a sequence of regions. Ultimately, the final image is extracted from a sequence of images. To test the proposed method, the experiment is carried out on the OSU thermal bench mark database images. The enhanced image results have been compared with the popular existing methods such as Histogram Equalization (HE) and Adaptive Histogram Equalization (AHE), max-median (3 × 3) using various evaluation measures. From the results, it is observed that the proposed method works better than the existing methods. © 2017 IEEE.

2017 Innovations in Power and Advanced Computing Technologies (i-PACT)

Adaptive new top-hat transform and multi-scale sequential toggle operator based infrared image enhancement

Informatics and Communication Technologies for Societal Development

Target Detection in Infrared Images Using Block-Based Approach

Studies in Informatics and Control

Generalization of Fuzzy C-Means based on Neutrosophic Logic

Infrared Physics & Technology

An improved infrared dim and small target detection algorithm based on the contrast mechanism of human visual system

A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization

Introduction to Data Compression

Mathematical Preliminaries for Lossless Compression

Journal	Data powered by TypesetTransactions on Computational Science XXV Lecture Notes in Computer Science
Publisher	Data powered by TypesetSpringer Berlin Heidelberg
ISSN	0302-9743
Open Access	0