Restoration of heat haze in image and video based on DT-CWT image fusion

There is a natural distortion effect that seen from long-range imaging systems occurs in hot airs causes to see defocusing images. It is known as heat haze, heat scintillation, mirage or atmospheric turbulence. In order to mitigate these effects, a set of steps are applied, and in an image fusion step, model-based restoration technique which is DT-CWT (Dual Tree Complex Wavelet Transform), with directional selectivity and shift-invariance properties, against other wavelet transforms, is used. In this work, both pixel-based and region-based image fusion methods are used for restoration. More than one distorted input was used in order to get one cleared image and then video result is also obtained from more than one output frame by shifting successive input frames. Both image and video results are compared with human-based visual system and FR (Full Reference)/ NR (Non-Reference) quality metrics. For comparison, the algorithm that bult-in our camera is also used with our pixel-based and region-based restoration methods for three different distances of scenes.

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Published
2024-11-20
DOI
https://doi.org/10.1117/12.3033352
Primary Topic
Advanced Image Fusion Techniques
Type
article
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article

Restoration of heat haze in image and video based on DT-CWT image fusion

Ender M. Ekşioğlu, Özlem Alpergün Tanas
Advanced Image Fusion Techniques
article

Restoration of heat haze in image and video based on DT-CWT image fusion

Ender M. Ekşioğlu, Özlem Alpergün Tanas
article en

Abstract

There is a natural distortion effect that seen from long-range imaging systems occurs in hot airs causes to see defocusing images. It is known as heat haze, heat scintillation, mirage or atmospheric turbulence. In order to mitigate these effects, a set of steps are applied, and in an image fusion step, model-based restoration technique which is DT-CWT (Dual Tree Complex Wavelet Transform), with directional selectivity and shift-invariance properties, against other wavelet transforms, is used. In this work, both pixel-based and region-based image fusion methods are used for restoration. More than one distorted input was used in order to get one cleared image and then video result is also obtained from more than one output frame by shifting successive input frames. Both image and video results are compared with human-based visual system and FR (Full Reference)/ NR (Non-Reference) quality metrics. For comparison, the algorithm that bult-in our camera is also used with our pixel-based and region-based restoration methods for three different distances of scenes.

Istanbul Technical University (TR), Aselsan (Turkey) (TR)
Openalex Percentile: Top 68%
Advanced Image Fusion Techniques
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