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Proceedings ArticleDOI

Infrared and Visible Image Fusion Based on CLAHE and Sparse Representation

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TLDR
A fusion method based on CLAHE and sparse representation is proposed, which can effectively extract the texture detail information of visible image and infrared image and can obtain state-of-the-art performance than DWT and NSCT algorithm.
Abstract
Image fusion is the method of merging information from many images of the same scene taken from various sensors. In this paper, a fusion method based on CLAHE and sparse representation is proposed, which can effectively extract the texture detail information of visible image and infrared image. Firstly, CLAHE and adaptive smoothing filtering is aimed to improve the contrast of the image. Sparse representation is aimed to fuse visible and infrared image. Experimental results show that the proposed algorithm can obtain state-of-the-art performance than DWT and NSCT algorithm.

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Citations
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Journal ArticleDOI

Real-Time CLAHE Algorithm Implementation in SoC FPGA Device for 4K UHD Video Stream

TL;DR: The CLAHE algorithm can be a component of a larger vision system, such as in autonomous vehicles or drones, but it can also support the analysis of underwater, thermal, or medical images both by humans and in an automated system.
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The Development of a Cost-Effective Imaging Device Based on Thermographic Technology

TL;DR: In this paper , the authors describe the development of a low-cost imaging device based on thermographic technology, which is capable of enhancing RAW high dynamic thermal readings obtained from the sensor using a computationally efficient image enhancement algorithm and presenting its visual result on the integrated OLED display.
References
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Deep learning for pixel-level image fusion: Recent advances and future prospects

TL;DR: This survey paper presents a systematic review of the DL-based pixel-level image fusion literature, summarized the main difficulties that exist in conventional image fusion research and discussed the advantages that DL can offer to address each of these problems.
Journal ArticleDOI

A survey on region based image fusion methods

TL;DR: A first hand classification of region based fusion methods is carried out and a comprehensive list of objective fusion evaluation metrics is highlighted to compare the existing methods.
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Adaptive mammographic image enhancement using first derivative and local statistics

TL;DR: An adaptive image enhancement method for mammographic images, which is based on the first derivative and the local statistics, so that image details can be enhanced and image noises can be suppressed.
Proceedings ArticleDOI

A fast and adaptive method for image contrast enhancement

TL;DR: A fast approach for image contrast enhancement, based on localized contrast manipulation, which is not only last and easy to implement, but also has several other promising properties (adaptive, multiscale, weighted localization, etc.).
Journal ArticleDOI

Simultaneous image fusion and super-resolution using sparse representation

TL;DR: A novel framework for simultaneous image fusion and super-resolution based on the use of sparse representations is proposed, and consists of three steps: low-resolution source images are interpolated and decomposed into high- and low-frequency components, and sparse coefficients from these components are computed and fused by using image fusion rules.
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