Automatic Face Enhancement Technique using Sigmoid Normalization based on Single Scale Retinex (SSR) Algorithm

Baskar, A.; Kumar, T. Gireesh

doi:10.1504/ijaip.2021.10030669

Cited by 2 publications

(2 citation statements)

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“…where S(x, y) represents the initial image, L(x, y) represents the data image after adaptive median filtering [12], and R(x, y) represents the reflection image. Retinex can be obtained by merging and converting the above-given three images into the corresponding number field:…”

Section: Image Brightness Enhancementmentioning

confidence: 99%

Retinex Algorithm and Mathematical Methods Based Texture Detail Enhancement Method for Panoramic Images

Kang

2022

Mathematical Problems in Engineering

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A panoramic image texture detail enhancement method based on the Retinex algorithm is proposed to work on the nature of panoramic images. Firstly, the panoramic image is collected, then the panoramic image is preprocessed through brightness enhancement, the brightness of the preprocessed panoramic image is normalized, and the panoramic image is optimized and increased by the improved Retinex algorithm. Finally, the simulation test of the panoramic image was carried out. The results show that the improved Retinex algorithm works on the sign to-commotion proportion of the panoramic image. Furthermore, the time required to enhance the panoramic texture detail is short, which can meet the practical requirements of panoramic image subsequent processing.

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Section: Image Brightness Enhancementmentioning

confidence: 99%

Retinex Algorithm and Mathematical Methods Based Texture Detail Enhancement Method for Panoramic Images

Kang

2022

Mathematical Problems in Engineering

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“…The Retinex algorithm is a commonly used image enhancement method whose core idea is to adjust the contrast and brightness of an image while preserving image details. Improved versions of the Retinex algorithm include Single Scale Retinex (SSR) [1] , Multi-Scale Retinex (MSR) [2] and Multi-Scale Retinex with Color Restoration (MSRCR) [3] .…”

Section: Introductionmentioning

confidence: 99%

Low-Light Road Disease Detection Algorithm Based on YOLOv8

Yin,

Kang,

Yang

et al. 2024

Advances in Transdisciplinary Engineering

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China has an extensive road network, thus requiring daily maintenance. During the collection of road defect data sets, scenarios with low illumination or extreme lack of light may occur. In such environments, the quality of image collection can be significantly reduced due to the low visibility of the surrounding environment, leading to the absence of intricate details. These challenges can negatively impact subsequent intricate visual tasks, including object detection and defect recognition utilizing road dataset images, thereby diminishing the precision and efficiency of the recognition process. Therefore, this paper adopts the Retinex algorithm to enhance low-illumination road images and performs road defect detection on the enhanced images, significantly improving the detection accuracy. An enhanced YOLOv8 detection algorithm is introduced to boost the detection efficiency of road defects. This updated algorithm incorporates FasterNet as the feature extraction network, resulting in improved computational speed. Integrating the Deformable-LKA module in the Neck layer can enhance the detection capability for small and irregularly shaped objects. RFAConv, a combination of spatial attention mechanisms and convolution operations, is employed to enhance the detection head and amplify the model’s feature extraction capabilities.The introduced algorithm model undergoes training, validation, and testing procedures on road defect datasets, while also being evaluated against other algorithm models for comparison. The improved algorithm model can achieve accurate recognition of road defects.

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Automatic Face Enhancement Technique using Sigmoid Normalization based on Single Scale Retinex (SSR) Algorithm

Cited by 2 publications

References 0 publications

Retinex Algorithm and Mathematical Methods Based Texture Detail Enhancement Method for Panoramic Images

Retinex Algorithm and Mathematical Methods Based Texture Detail Enhancement Method for Panoramic Images

Low-Light Road Disease Detection Algorithm Based on YOLOv8

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