Digital Image Enhancement Using Enhanced Detail and Dehaze Technique (DDE)

Yao, Danny Ngo Lung; Abdullah, Baharudin; Suaib, Norhaida Mohd; Sulaiman, Hamzah Asyrani

doi:10.1166/asl.2018.11108

Cited by 6 publications

(1 citation statement)

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“…The proposed detail enhancement exposure fusion algorithm can better preserve the details in the saturated region. In [6,7], the author proposed a low-illumination image enhancement algorithm. The article finally got an image with enhanced details and suitable for brightness.…”

Section: Introductionmentioning

confidence: 99%

Multi-Feature Fusion Algorithm in VR Panoramic Image Detail Enhancement Processing

Zhu

2020

IEEE Access

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VR panoramic image is an image imaging technology that covers a wide range of scenes. Its imaging range is much larger than that of traditional imaging systems, and it can fully reflect all the information of the imaging space. However, the current VR panoramic images have the problems that the details are not obvious enough and the processing is not comprehensive enough. In view of the shadow problem in VR panoramic images, this paper proposes a multi-feature fusion VR panoramic image shadow elimination algorithm, which uses HSV color features and LBP / LSFP texture features to obtain shadow detection results, and then obtains the final detection results by fusion. The experimental results prove that while ensuring a low missed detection rate, the false detection rate is greatly reduced. The comprehensive evaluation index Avg in this paper is improved by 3.4% compared with the shadow elimination algorithm based on a single feature. This paper proposes an image saliency detection algorithm and image detail enhancement algorithm based on multi-feature fusion. The final saliency map is obtained through linear fusion. Experiments prove that the image detail enhancement algorithm based on multi-feature fusion mentioned in this paper has achieved very good results. This paper compares the performance of single-feature and multi-feature fusion algorithms. HSV, LBP and LSFP obtain 93.39% accuracy and 0.8708 correlation coefficient. The effect of multi-fusion fusion is better than that of single feature.

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Section: Introductionmentioning

confidence: 99%

Multi-Feature Fusion Algorithm in VR Panoramic Image Detail Enhancement Processing

Zhu

2020

IEEE Access

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Traffic Image Dehazing Based on Wavelength Related Physical Imaging Model

Wang

Yin

Zheng

2020

Lecture Notes in Computer Science

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Improved Social Force Model for Emergency Evacuation Scene with Limited Field of Vision

Zhou

Feng

Tai

et al. 2021

J. Phys.: Conf. Ser.

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Pedestrian movement modeling and simulation is an important way to formulate an emergency evacuation plan. The performance of the pedestrian movement model directly determines the accuracy of the simulation experiment results. Pedestrian movement in the real world is a very complicated process, and this process is susceptible to a variety of external factors (e.g. road conditions, visibility, etc.) and internal factors (e.g. psychological states, etc.) which making it difficult to model pedestrian movement. The social force model draws on the principles of mechanics and proposes a modeling scheme from the perspective of social force which greatly simplifies the process of pedestrian movement modeling. However, the traditional social force model considers the general situation of pedestrian movement and does not target the emergency evacuation scene, which has certain limitations. In this paper we start with the social force model and introduces the concepts of external guides and internal panic emotions to improves the model. In the scene, the influence of the attraction of the guide and the psychological state of the pedestrian on the movement process of the pedestrian are considered. So that the model is more suitable for the emergency evacuation scene with limited field of vision. It also provides a reference for emergency evacuation plans in public places. We take the subway station as the research object and uses Anylogic software to build simulation experiments. The experimental results show that the improved model we proposed in this paper is less than the traditional model in terms of evacuation time by 8.4%, and is better than the traditional model in terms of exit pedestrian density by 21.5%.

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Digital Image Enhancement Using Enhanced Detail and Dehaze Technique (DDE)

Cited by 6 publications

References 0 publications

Multi-Feature Fusion Algorithm in VR Panoramic Image Detail Enhancement Processing

Multi-Feature Fusion Algorithm in VR Panoramic Image Detail Enhancement Processing

Traffic Image Dehazing Based on Wavelength Related Physical Imaging Model

Improved Social Force Model for Emergency Evacuation Scene with Limited Field of Vision

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