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The existing rain streaks removal methods provide better deraining results, but it cannot be implemented on the low-light images due to the poor visual quality. To solve this problem, this paper presents a novel rain streaks removal approach using ...${}^{\mathit{}}$

In this paper, we propose an advanced variational model for image segmentation and bias correction. In contrast to the majority of existing level set segmentation models that only consider illumination bias fields, we additionally consider the ...

• A novel image segmentation model based on image structural prior is introduced.
• An adaptive regularization constraint for adaptive restoration of image intensity.
• The model is robust to images with noise and intensity ...

Dental periapical lesions, commonly associated with inflammation around the tooth apex, pose a significant challenge in early diagnosis and treatment. This study introduces a novel approach for the detection of dental periapical lesions through ...

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• Innovative approach to address the challenges associated with detection of dental periapical lesions.
• Integration of Retinex algorithm to overcome inconsistent illumination improving radiographic image.
• Tailored lightweight deep ...

Image dedusting has gained increasing attention as a preprocessing step for computer vision tasks. Current traditional image dedusting methods rely on a variety of constraints or priors, which are easy to be limited in real complex dusty scenes. ...

• DeustGAN based on Retinex with GANs can train with unpaired clear-dusty images.
• we proved the significant dust removal performance of the Retinex.
• DedustGAN designed a no-reference fusion strategy for various enhancement tasks.

This article proposes a new method Maximum Decomposition Diffusion Enhancement(MDDE) for low light image enhancement. This method combines the advantages of Retinex theory and diffusion models, making the model physically interpretable and improving the ...

Low-light image enhancement (LLIE) is mainly used to restore image degradation caused by environmental noise, lighting effects, and other factors. Despite many relevant works combating environmental interference, LLIE currently still faces ...

Improving the quality of low-light images is a fundamental task with vast applications in computer vision. Retinex-based methods which decompose the images into reflectance and illumination components have been actively studied over the past ...

An efficient model to detect and track the objects in adverse weather is proposed using Tanh Softmax (TSM) EfficientDet and Jaccard Similarity based Kuhn-Munkres (JS-KM) with Pearson-Retinex in this paper. The noises were initially removed using ...

Images taken under poor lighting conditions generally present problems such as low brightness, noise, and color distortion, so dealing with low-light images is challenging. To solve this problem, current mainstream methods focus on designing ...

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• The proposed algorithm focuses on embedding prior knowledge into the network to assist the low-light image enhancement.
• An effective loss function is designed to balance the color distortion and noise suppression.
• Our model can be ...

Underwater images suffer from color cast and low contrast due to the light absorption and scattering. Especially when natural light is not sufficient, large dark areas appear in the captured image, making it impossible to understand the image ...

With the increasing popularity of full-screen devices, phone manufacturers have started placing cameras behind screens to increase the percentage of the displays. However, this innovative approach, known as under-display camera (UDC) technology, ...

Current Retinex-based image enhancement methods with fixed scale filters cannot adapt to situations involving various depths of field and illuminations. In this paper, a simple but effective method based on adaptive full-scale Retinex (AFSR) is ...

• We propose to divide image gradients into image contours and textural gradients according to whether they belong to the groups of connected gradients with ...

Retinex theory was first proposed by Land and McCann [1], where retinex is a portmanteau derived from the words of retina and cortex, implying that both the retina and cerebral cortex may participate in the perception of lightness and ...

Most low-light image enhancement methods only adjust the brightness, contrast and noise reduction of low-light images, making it difficult to recover the lost information in darker areas of the image, and even cause color distortion ...

• We construct a novel global attention module to solve the problem of reusing the weights of channel weight feature maps at different locations of the same ...

Capturing images in weak illumination environments seriously degrades image quality, such as low visibility, low contrast, artifacts, and noise. Solving a series of degradation of low-light images can effectively improve the visual ...

• A new fully convolutional network for low-light image enhancement.
• A “Deep-...

Directly fusing the low-light visible and infrared images is hard to obtain fusion results containing rich structural details and critical infrared targets, due to the limitations of extreme illumination. The generated fusion results are typically ...

In retinex model, images are considered as a combination of two components: illumination and reflectance. However, decomposing an image into the illumination and reflectance is an ill-posed problem. This paper presents a new approach to estimate ...

Underwater image enhancement has been attracting much attention due to its significance in marine engineering and aquatic robotics. Captured underwater images usually suffer from contrast degradation, low illumination, color cast, and noise. Many ...

To accurately identify the dynamically changing water level in the ship's cabin, the Retinex algorithm is improved by using the bilateral filtering method firstly, which enhances the cabin image at the edge of the liquid level. then the image is ...

In this paper, we explore the problem of single-image haze removal based on retinex model and new deep retinex decomposition architecture. Reformulating dehazing as reverse retinex, we propose a depth-guided retinex decomposition network, which ...