scholarly journals Design of the Poster Image System Based on Human Vision

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiaolifei Sun
Keyword(s):  
Image Enhancement ◽  
Dynamic Range ◽  
Incident Light ◽  
Color Constancy ◽  
Visual Features ◽  
Compressed Domain ◽  
Light Component ◽  
Reflected Light ◽  
Perception System ◽  
Retinex Theory

At present, the human visual perception system is the most effective, accurate, and fast image processing system in the world. This is because human eyes have some special visual features, but the features closely related to image enhancement include color constancy and brightness constancy. This paper presents a new image enhancement framework and computational model which can better simulate human visual features. It is based on the analysis of color constancy and luminance constancy and Retinex theory. And, this is a new image enhancement method in the compressed domain based on Retinex theory. In Retinex theory, DCT coefficients consist of incident components (DC coefficients) and reflection components (AC coefficients). By adjusting the dynamic range of DC coefficients, carefully adjusting AC coefficients, and using the threshold method for block suppression, the compressed domain image can be enhanced. On the basis of Retinex theory, the incident light and reflected light components are considered synthetically, the dynamic range (DC coefficient) of the incident light component and the details of the reflected light component (AC coefficient) are adjusted, and then the incident light component is reexamined. Moreover, it achieves a better image enhancement effect and avoids the blocking effect.

A Modified Multi Scale Retinex with Color Restoration Algorithm for Automatic Enhancement of Landsat-5 Remote Sensing Image

2011 ◽  
Vol 341-342 ◽  
pp. 893-897
Author(s):  
Gui Zhou Wang ◽  
Guo Jin He
Keyword(s):  
Image Enhancement ◽  
Dynamic Range ◽  
Color Constancy ◽  
Human Perception ◽  
Histogram Equalization ◽  
Image Processing Algorithm ◽  
Multi Scale ◽  
Dynamic Range Compression ◽  
Restoration Algorithm ◽  
Color Restoration

The retinex is a human perception based image processing algorithm which provides color constancy and dynamic range compression. The multi scale retinex with color restoration (MSRCR) has shown itself to be a very versatile automatic image enhancement algorithm that simultaneously provides dynamic range compression, color constancy, and color rendition. But the MSRCR results suffer from lower global brightness and partial color distortion. In order to improve the MSRCR method, this paper presents a modified MSRCR algorithm to Landsat-5 image enhancement considering percent liner stretch and histogram adjustment. Finally, the effect of modified MSRCR method on Landsat-5 image enhancement is analyzed and the comparison with other color adjustment methods such as gamma correction and histogram equalization is reported in the experimental results.

scholarly journals Underwater image enhancement method with non-uniform illumination based on Retinex and ADMM

2021 ◽  
Vol 39 (4) ◽  
pp. 824-830
Author(s):  
Weidong Liu ◽  
Jiyu Li ◽  
Wenbo Zhang ◽  
Le Li
Keyword(s):  
Image Enhancement ◽  
Color Constancy ◽  
Bilateral Filter ◽  
Uniform Illumination ◽  
Illumination Problem ◽  
Underwater Image ◽  
Augmented Lagrange Multiplier ◽  
Enhancement Method ◽  
Retinex Theory ◽  
Enhancement Algorithm

In order to solve the image blurring and distortion problem caused by underwater non-uniform and low illumination, this paper proposes an underwater image enhancement algorithm based on the Retinex theory and the Alternating Direction Method of Multipliers (ADMM). Firstly, the L component of the original image in the Lab space is extracted as the initial illumination map, and an Augmented Lagrange Multiplier (ALM) framework is constructed based on the ADMM to optimize the initial illumination map in order to obtain an accurate illumination image. In addition, the illumination map is further corrected in the luminance region with the Gamma Correction. Secondly, combined with the color constancy characteristics in the Retinex theory, the reflected image of the object is obtained. Finally, the bilateral filter is picked to suppress the underwater noise and obtain a more detailed enhanced image. The experimental results show that the underwater image enhancement algorithm can effectively solve the non-uniform illumination problem caused by natural light or artificial light source and improve the underwater image quality, thus having a better performance than other algorithms.

An Improved Algorithm Based on Retinex Theory for X-Ray Medical Image

2013 ◽  
Vol 772 ◽  
pp. 233-238
Author(s):  
Wen Bo Wang ◽  
Li Juan Zhou ◽  
Li Fei
Keyword(s):  
Image Enhancement ◽  
Medical Image ◽  
Dynamic Range ◽  
Medical Image Analysis ◽  
Practical Significance ◽  
Low Contrast ◽  
X Ray ◽  
Retinex Algorithm ◽  
Retinex Theory ◽  
Medical Image Enhancement

Retinex theory combined the elements of images and visual.This paper improved the Retinex-based medical image enhancement method, It can get better brightness by using the neural network logarithmic The S-shaped LogSig transfer function instead of the original MSR logarithm function. Based on this, the paper presents a composite LRA (LogSig Retinex Algorithm) algorithm, and analysed the shortcomings of the original Retinex algorithm applied to the X-ray medical image analysis, described the advantage of the composite LRA algorithm is better than traditional Retinex algorithm on the X-ray medical image. Experimental results show that the improved Retinex algorithm can achieve not only low-contrast medical image enhancement, but also the dynamic range compression of the image, can significantly improve the information of the medical image of the dark area. It has practical significance for clinical diagnosis.

scholarly journals Retinex Based Image Enhancement via General Dictionary Convolutional Sparse Coding

2020 ◽  
Vol 10 (12) ◽  
pp. 4395
Author(s):  
Jongsu Yoon ◽  
Yoonsik Choe
Keyword(s):  
Visual System ◽  
Image Enhancement ◽  
Sparse Coding ◽  
Human Visual System ◽  
Color Constancy ◽  
Large Dataset ◽  
Learned Dictionary ◽  
Retinex Theory ◽  
The Difference ◽  
Value Decomposition

Retinex theory represents the human visual system by showing the relative reflectance of an object under various illumination conditions. A feature of this human visual system is color constancy, and the Retinex theory is designed in consideration of this feature. The Retinex algorithms have been popularly used to effectively decompose the illumination and reflectance of an object. The main aim of this paper is to study image enhancement using convolution sparse coding and sparse representations of the reflectance component in the Retinex model over a learned dictionary. To realize this, we use the convolutional sparse coding model to represent the reflectance component in detail. In addition, we propose that the reflectance component can be reconstructed using a trained general dictionary by using convolutional sparse coding from a large dataset. We use singular value decomposition in limited memory to construct a best reflectance dictionary. This allows the reflectance component to provide improved visual quality over conventional methods, as shown in the experimental results. Consequently, we can reduce the difference in perception between humans and machines through the proposed Retinex-based image enhancement.

scholarly journals Electrical tuning of the polarization state of light using graphene-integrated anisotropic metasurfaces

2017 ◽  
Vol 375 (2090) ◽  
pp. 20160061 ◽  
Author(s):  
Shourya Dutta-Gupta ◽  
Nima Dabidian ◽  
Iskandar Kholmanov ◽  
Mikhail A. Belkin ◽  
Gennady Shvets
Keyword(s):  
Tilt Angle ◽  
Incident Light ◽  
Polarization State ◽  
Dynamic Control ◽  
Single Layer ◽  
Single Layer Graphene ◽  
Dynamic Polarization ◽  
Reflected Light ◽  
Electro Optic ◽  
The Way

Plasmonic metasurfaces have been employed for moulding the flow of transmitted and reflected light, thereby enabling numerous applications that benefit from their ultra-thin sub-wavelength format. Their appeal is further enhanced by the incorporation of active electro-optic elements, paving the way for dynamic control of light's properties. In this paper, we realize a dynamic polarization state generator using a graphene-integrated anisotropic metasurface (GIAM) that converts the linear polarization of the incident light into an elliptical one. This is accomplished by using an anisotropic metasurface with two principal polarization axes, one of which possesses a Fano-type resonance. A gate-controlled single-layer graphene integrated with the metasurface was employed as an electro-optic element controlling the phase and intensity of light polarized along the resonant axis of the GIAM. When the incident light is polarized at an angle to the resonant axis of the metasurface, the ellipticity of the reflected light can be dynamically controlled by the application of a gate voltage. Thus accomplished dynamic polarization control is experimentally demonstrated and characterized by measuring the Stokes polarization parameters. Large changes of the ellipticity and the tilt angle of the polarization ellipse are observed. Our measurements show that the tilt angle can be changed from positive values through zero to negative values while keeping the ellipticity constant, potentially paving the way to rapid ellipsometry and other characterization techniques requiring fast polarization shifting. This article is part of the themed issue ‘New horizons for nanophotonics’.

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