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Research on low illumination coal gangue image enhancement based on improved retinex algorithm

INTERNATIONAL JOURNAL OF COAL PREPARATION AND UTILIZATION 2023年第6期43卷 999-1015页

作者： Shang, Deyong Yang, Zhiyuan Zhang, Xi Zheng, Linlin Lv, Zhibin China Univ Min & Technol Beijing Sch Mech Elect & Informat Engn Beijing Peoples R China China Univ Min & Technol Beijing Intelligent Min & Robot Res Inst Beijing Peoples R China Key Lab Intelligent Min & Robot Minist Emergency Management Beijing Peoples R China Jinan Ecological Environm Monitoring Ctr Shandong Jinan Peoples R China

Aiming at the problems of coal and gangue image recognition in low illumination or high dust concentration environment, an adaptive enhancement method based on improved retinex algorithm, is proposed: H-GF-MSR algorithm. The algorithm is processed in HSV color space, uses guided filter for multi-scale retinex algorithm in brightness component, and carries out adaptive saturation stretching in saturation component. Then the images are processed by histogram equalization, and the two algorithms are fused to improve the accuracy. Compared with SSR algorithm, MSRCR algorithm and other classical algorithms, this algorithm is improved in suppressing the generation of halo and image edge enhancement. The experimental results show that in terms of image evaluation indexes such as information entropy, image mean, image average gradient and peak signal-to-noise ratio, compared with SSR algorithm, the algorithm improves by 5.4%, 41.1%, 33.2% and 0.4% respectively;compared with MSRCR algorithm, the average improvement is 2.9%, 32.4%, 31.7% and 0.7% respectively. Through the enhancement experiments of coal gangue image in the illumination range of 10 lux similar to 200 lux, the algorithm has better enhancement effect. It can effectively suppress the bright light and restore the original details of the object.

关键词： Low illumination coal gangue recognition retinex algorithm guided filtering image enhancement

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Autonomous robot navigation using retinex algorithm for multiscale image adaptability in low-light environment

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INTELLIGENT SERVICE ROBOTICS 2019年第4期12卷 359-369页

作者： Wen, Shuhuan Hu, Xueheng Ma, Jinrong Sun, Fuchun Fang, Bin Yanshan Univ Key Lab Ind Comp Control Engn Hebei Prov Qinhuangdao Hebei Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China

This paper proposes an improved retinex theory based on a weighted guided filter method to enhance images in low-light conditions. The captured images under low illumination can cause dimness, distortion or details loss. We use the weighted guided filter method to perform illumination estimation and the original image is regarded as the guidance image, which can avoid color distortion and over-enhancement. It can adjust the regularization parameter adaptively based on the image content. Perceptual contrast is improved by using an illumination enhancement method with dynamic adjustment. To test the validness of our algorithm, the weighted guided filter method proposed in this paper is compared with bilateral filter and the guided filter method. Finally, experiment under low illumination is implemented on a NAO robot by using the proposed weighted guided filter method based on EKF-SLAM. The experiment result demonstrates that the proposed weighted guided filter method is feasible and effective in low-light environment.

关键词： Image enhancement retinex algorithm Weighted guided filter Reflection extraction Landmark recognition

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Modelling the microstructure random fields of soft soil under the scale optimized retinex algorithm and microscopic image enhancement

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2017年第5期33卷 2913-2923页

作者： Huang, Linchong Tao, Chenyuan Yu, Jindong Huang, Shuai Liang, Yu Sun Yat Sen Univ Sch Engn Guangzhou 510006 Guangdong Peoples R China Guangdong Construct Polytech Guangzhou Guangdong Peoples R China

The mechanical properties of the geo-materials are greatly affected by the internal micro structure system. Multi-scale modelling and analysis are considered as an effective tool for revealing the mechanical process. Aiming at the problems of the light intensity decrease and the uneven illumination, a retinex scale optimized image enhancement algorithm is proposed, based on the light reflection model and retinex theory. Based on the retinex theory, a Monte-Carlo random geometric numerical model of the microstructure is established, with some soil specimens in South China as the study object. After that, three-axis consolidation process of soft soil materials are simulated, which are compared with the experimental data. The results showthat: the retinex scale optimized image enhancement algorithm can accurately estimate the illumination component, eliminate the influence of the uneven illumination, improve the contrast of image and retain the details of the microstructure simultaneously. The random field model with this algorithm is simple and effective, the image becomes clearer, and the contrast ratio is improved, after using retinex algorithm to enhance the CT image of rock and soil. The threshold segmentation of the enhanced image, and the fidelity between the enhanced image and the original image, are higher than that of the homomorphic filtering method and histogram equalization method, which explained that the algorithm could preserve the microstructure information of the micro image well. The result of numerical simulation is similar with the one obtained from conventional three axis consolidation test, which proves that the simulation result is reliable.

关键词： Rock and soil materials microstructure random field scale optimization retinex algorithm

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A Low-Cost and High-Throughput FPGA Implementation of the retinex algorithm for Real-Time Video Enhancement

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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2020年第1期28卷 101-114页

作者： Park, Jin Woo Lee, Hyokeun Kim, Boyeal Kang, Dong-Goo Jin, Seung Oh Kim, Hyun Lee, Hyuk-Jae Seoul Natl Univ Dept Elect & Comp Engn Inter Univ Semicond Res Ctr Seoul 08826 South Korea Korea Electrotechnol Res Inst RSS Ctr Ansan 15588 South Korea Seoul Natl Univ Sci & Technol Dept Elect & Informat Engn Seoul 01811 South Korea Seoul Natl Univ Sci & Technol Res Ctr Elect & Informat Technol Seoul 01811 South Korea

For video applications in a special environment such as medical imaging, space exploration, and underwater exploration, the video captured by an image sensor is often deteriorated because of low lighting conditions. Therefore, it is necessary to enhance the part of the image that is too dark to distinguish details while maintaining the remaining part with the same brightness. The retinex algorithm is widely used to restore naturalness of a video, especially exhibiting outstanding performance in the enhancement of a dark area. However, it demands large computational complexity because of its intricate structure, such as the Gaussian filter and exponentiation operations, and consequently, it is difficult to process in real time. This article presents a low-cost and high-throughput design of the retinex video enhancement algorithm. The hardware (HW) design is implemented using a field-programmable gate array (FPGA), and it supports a throughput of 60 frames/s for a 1920 x 1080 image with negligible latency. The proposed FPGA design minimizes HW resources while maintaining the quality and the performance by using a small line buffer instead of a frame buffer, by applying the concept of approximate computing for the complex Gaussian filter, and by designing a new and nontrivial exponentiation operation. The proposed design makes it possible to significantly reduce HW resources (up to 79.22% of total resources) compared to existing systems and is compatible with commercialized devices through the standard HDMI/DVI video ports.

关键词： Approximate computing field-programmable gate array (FPGA) implementation low-cost implementation real-time implementation retinex algorithm video enhancement

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A new underwater image enhancement algorithm based on adaptive feedback and retinex algorithm

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MULTIMEDIA TOOLS AND APPLICATIONS 2021年第18期80卷 28487-28499页

作者： Tang, Zhijie Jiang, Lizhou Luo, Zhihang Shanghai Univ Sch Mechatron Engn & Automat 99 Shangda Rd Shanghai Peoples R China

Due to the serious attenuation and scattering effects of light underwater, actual underwater images have problems such as low contrast and color distortion. This paper proposes an underwater image enhancement algorithm. First, we apply the guided filtering to the algorithm improvement to get the improved image. Then, the image is converted from RGB color space to HSI space, and the three components of hue, saturation, and intensity are separated. Then use adaptive feedback adjustment to achieve the stretching of saturation and linear enhancement of intensity. Then the image is converted from the HSI color space back to the RGB color space to obtain an enhanced image. Finally, the improved image and the enhanced image are merged at the pixel level. After experimental analysis and comparison, the time required for guided filtering to process images can be reduced by 65%, the structural similarity can reach more than 90%, and the peak signal-to-noise ratio and information entropy have been greatly improved. From a visual point of view, the color saturation, color richness, local contrast and clarity of the image have all been significantly improved.

关键词： Underwater image Image fusion Image enhancement retinex algorithm Adaptive adjustment

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Novel retinex algorithm by interpolation and adaptive noise suppression

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Journal of Central South University 2012年第9期19卷 2541-2547页

作者：李武劲古博黄江涛王明辉 College of Computer Science Sichuan University College of Computer and Information Engineering Guangxi Teachers Education University Key Laboratory of Scientific Computing and Intelligent Information Processing of Guangxi Province (Guangxi University)

In order to improve image quality, a novel retinex algorithm for image enhancement was presented. Different from conventional algorithms, it was based on certain defined points containing the illumination information in the intensity image to estimate the illumination. After locating the points, the whole illumination image was computed by an interpolation technique. When attempting to recover the reflectance image, an adaptive method which can be considered as an optimization problem was employed to suppress noise in dark environments and keep details in other areas. For color images, it was taken in the band of each channel separately. Experimental results demonstrate that the proposed algorithm is superior to the traditional retinex algorithms in image entropy.

关键词： retinex algorithm illumination estimation interpolation adaptive noise suppression

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Color image enhancement algorithm based on improved retinex algorithm

Color image enhancement algorithm based on improved Retinex ...

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Asia Conference on algorithms, Computing and Machine Learning (CACML))

作者： Gao, Yuhang Su, Chuhao Xu, Zhaoheng Beijing Univ Posts & Telecommun Sch Comp Sci Natl Pilot Software Engn SchoolBUPT Beijing Peoples R China Beijing Univ Posts & Telecommun BUPT Beijing Peoples R China

ISBN: (数字)9781665482905

ISBN: (纸本)9781665482905

In order to solve the problem of low expressiveness caused by color distortion and poor saturation when performing image enhancement with classic retinex algorithm, this paper proposes a color image enhancement algorithm base on the improved retinex algorithm. In this algorithm, the input image is decomposed into illumination component and reflection component base on retinex theory first, then logarithmic transformation and Gaussian filtering are performed on the illumination component of HSV color space to approximate the visual system's perception intensity to physical reflectance. Next, the estimated illumination value of scene is used to adjust the multi-scale reflection components of the input image, and to obtain a preliminarily enhanced image. Finally, a color correction factor is introduced into the initial enhanced image to obtain the final enhanced image base on gray world hypothesis. Experimental results show that compared with several classical retinex algorithms, the proposed algorithm can effectively improve the brightness, contrast and visual information fidelity of the input image without color distortion.

关键词： image Enhancement retinex algorithm improved Grayscale World hypothesis

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TONE MAPPING METHOD BASED ON retinex algorithm USING THRESHOLD FUNCTION 5

TONE MAPPING METHOD BASED ON RETINEX ALGORITHM USING THRESHO...

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2016 5th IEEE International Conference on Network Infrastructure and Digital Content(IC-NIDC 2016)

作者： Heungsoo Kim Seungwoo Wee Jechang Jeong Department of Electronics and Computer Engineering Hanyang University

ISBN: (纸本)9781509012473

In this paper,we proposed tone mapping method which uses threshold *** was impossible for conventional Multi-Scale retinex algorithm to express detail parts due to damage in bright region of dynamic range at compression *** reduce the damage,which occurs in tone mapping process,by setting the threshold of Log Scale image in this *** experimental tests demonstrated that proposed algorithm reserves detailed information and significantly improves the quality of image,compared to conventional algorithms.

关键词： High dynamic range Tone mapping Threshold function retinex algorithm

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Unsupervised Monocular Depth Estimation Method Based on Uncertainty Analysis and retinex algorithm

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SENSORS 2020年第18期20卷 5389.-5389.页

作者： Song, Chuanxue Qi, Chunyang Song, Shixin Xiao, Feng Jilin Univ Coll Automot Engn Changchun 130022 Peoples R China Jilin Univ Sch Mech & Aerosp Engn Changchun 130022 Peoples R China Jilin Univ State Key Lab Automot Simulat & Control Changchun 130022 Peoples R China

Depth estimation of a single image presents a classic problem for computer vision, and is important for the 3D reconstruction of scenes, augmented reality, and object detection. At present, most researchers are beginning to focus on unsupervised monocular depth estimation. This paper proposes solutions to the current depth estimation problem. These solutions include a monocular depth estimation method based on uncertainty analysis, which solves the problem in which a neural network has strong expressive ability but cannot evaluate the reliability of an output result. In addition, this paper proposes a photometric loss function based on the retinex algorithm, which solves the problem of pulling around pixels due to the presence of moving objects. We objectively compare our method to current mainstream monocular depth estimation methods and obtain satisfactory results.

关键词： monocular depth estimation retinex algorithm uncertainty analysis

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LOW ILLUMINATION IMAGE retinex ENHANCEMENT algorithm BASED ON GUIDED FILTERING 3

LOW ILLUMINATION IMAGE RETINEX ENHANCEMENT ALGORITHM BASED O...

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3rd IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Yin, Jingcao Li, Hongbo Du, Junping He, Pengcheng Beijing Univ Posts & Telecommun Beijing Key Lab Intelligent Teleconnnun Software Beijing 100876 Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781479947195

It has been shown by retinex theory that the object's color in the image is determined by its reflectance. Under this frame work, several retinex-based algorithms have been developed to uncover the real appearance of objects by estimating their reflectance in image. In this paper we propose an algorithm of optimizing the illumination based on guided image filter theory, where bilateral filter is utilized to estimate the illumination image. The proposed algorithm removes the halo phenomenon precisely and strengthens the partial contrast gradient effectively. Examples are given to demonstrate the effectiveness of the proposed method.

关键词： image enhancement retinex algorithm guided filter Gamma correction

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