Visible and near‐infrared image fusion based on information complementarity by Zhuo Li, Shiliang Pu, Mengqi Ji, Feng Zeng, Bo Li

“…Then, to generate a guide map, the near‐infrared image with night adjustment was processed as well. …”
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Resolution-Enhancement for an Integral Imaging Microscopy Using Deep Learning by Ki-Chul Kwon, Ki Hoon Kwon, Munkh-Uchral Erdenebat, Yan-Ling Piao, Young-Tae Lim, Min Young Kim, Nam Kim

“…Then, a deep learning algorithm is used to generate maximum possible resolution for each reconstructed directional-view image with improved quality. …”
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Image dehazing based on double branch convolution and detail enhancement by ZHAI Fengwen, ZHU Yutong, JIN Jing

“…Because of detail loss, color distortion and contrast reduction in the image dehazing process in a haze condition, we proposed the image dehazing network based on double branch convolution and detail enhancement, which consists of image dehazing module and detail enhancement module. …”
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Reversible data hiding scheme based on enhanced image smoothness by Jinghan WANG, Hui ZHU, Helin LI, Hui LI, Xiaopeng YANG

“…With the prosperity of Internet technology and the popularity of social networks, reversible data hiding technology has been widely adopted in concealed information transmission of medical and military fields with its advantages on secret information recovery.Traditional reversible data hiding schemes mainly focus on the enhancement of embedding capacity and the reduction of the distortion rate of stego image, but pay less attention to the understanding of image details with the human eyes.Thus, it is difficult to resist hidden information detection methods.To solve the above challenge, a reversible data hiding algorithm was proposed, which ensured the visual quality of the stego image in the process of data hiding through the image visual smoothness enhancement.Specifically, the original image was divided into reference area and non-reference area.The secret data was embedded through the translation of the difference, which was calculated according to the predicted pixel value and the original pixel value of the non-reference area.To guarantee the visual quality of the image, smoothing mechanism was constructed, in which a Gaussian filter was utilized as a template to filter the predicted value and to add the filter difference into the cover image without loss.The pixel value of the reference region was used as edge information for lossless restoration of the original image.The filtering coefficient in Gaussian function was exploited as the embedded key to ensure the security of secret information.Simulation results regarding a large number of classical image data sets illustrated that the visual smoothness of stego image processed by this scheme was effectively enhanced with lower distortion rate, higher embedding rate, and higher embedding and extraction efficiency.In a typical circumstance, the similarity between the generated stego image and the Gaussian filter image can reach 0.9963.The PSNR and the embedded capacity can be up to 37.346 and 0.3289 BPP, respectively.…”
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A localization strategy combined with transfer learning for image annotation. by Zhiqiang Chen, Leelavathi Rajamanickam, Jianfang Cao, Aidi Zhao, Xiaohui Hu

“…The model consists of an InceptionV3 network pretrained on the ImageNet dataset and a label localization algorithm. …”
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COMPARATIVE ANALYSIS OF NO-REFERENCE MEASURES FOR DIGITAL IMAGE SHARPNESS ASSESSMENT by Y. I. Golub, F. V. Starovoitov, V. V. Starovoitov

“…Images obtained in various ways may have unsatisfactory quality; therefore, an important step in image processing and analysis algorithms is a quality control stage of the received data. …”
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Automatic magnetic resonance imaging series labelling for large repositories by Armando Gomis-Maya, Leonor Cerdá-Alberich, Diana Veiga-Canuto, Salvatore Claudio-Fanni, Amadeo Ten-Steve, Gloria Ribas-Despuig, Pedro José Mallol-Roselló, Joan Vila-Frances, Luis Marti-Bonmati

“…These results open the door to the automatic application of image post-processing and deep learning algorithms after accurate labeling, minimizing human intervention. …”
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Segmentation of Striatal Brain Structures from High Resolution PET Images by Ricardo J. P. C. Farinha, Ulla Ruotsalainen, Jussi Hirvonen, Lauri Tuominen, Jarmo Hietala, José M. Fonseca, Jussi Tohka

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Low-dimensional multiscale fast SAR image registration method by Jiamu Li, Wenbo Yu, Zijian Wang, Jiaxin Xie, Xiaojie Zhou, Yabo Liu, Zhongjun Yu, Meng Li, Yi Wang

“…Experiments on raw SAR images with neither prior information nor any pre-processing measure like terrain correction and de-speckling demonstrate the efficacy of the proposed method over other state-of-the-art SAR image registration algorithms. …”
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Camera Absolute Pose Estimation Using Hierarchical Attention in Multi-Scene by Xinhua Lu, Jingui Miao, Qingji Xue, Hui Wan, Hao Zhang

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Rapid Detection of Key Phenotypic Parameters in Wheat Grains Using Linear Array Camera by Wenjing Zhu, Kaiwen Duan, Xiao Li, Kai Yu, Changfeng Shao

“…A grain collection device utilizing a linear array camera was designed and constructed, accompanied by custom software to simplify device operation. Image processing was performed using Halcon image, enabling the development and implementation of a system for extracting key phenotypic parameters. …”
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Use of Sentinel-2 images for the detection of sandbars along the Lower Vistula by Klaudia Oktawia Kryniecka, Artur Magnuszewski

“…A proper selection of remote sensing index, creation of binary classification and selection of processing algorithm are important when detecting river islands. …”
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Advancing In Vivo Molecular Bioimaging With Optimal Frequency Offset Selection and Deep Learning Reconstruction for CEST MRI by Adarsha Bhattarai, Chathumi Samaraweera, Mariano Uberti, Aditya N. Bade, Yutong Liu, Dongming Peng

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Improving Mountainous DSM Accuracy Through an Innovative Opposite-Side Radargrammetry Algorithm by Jian Wang, Huiming Chai, Xiaoshuai Li, Xiaolei Lv

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Automatic wildfire monitoring system based on deep learning by Yingshu Peng, Yi Wang

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Smart Agriculture Applications and Data Analysis with Industry 4.0 by Abdullah Sevin, Yasin Ömercikoğlu

“…In the proposed image processing algorithm, the crops’ images were processed, weight estimates were made, and their numbers were taken. …”
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An Automatic Ear Temperature Monitoring Method for Group-Housed Pigs Adopting Infrared Thermography by Changzhen Zhang, Xiaoping Wu, Deqin Xiao, Xude Zhang, Xiaopeng Lei, Sicong Lin

“…In the second part of the study, the goal was to automatically extract the maximum and average values of the temperature in the ear region using morphological image processing and a temperature matrix. Our dataset (3600 pictures, 10,812 pig ears) was processed using 5-fold cross-validation before training the ear detection model. …”
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Fractal Analysis of Laplacian Pyramidal Filters Applied to Segmentation of Soil Images by J. de Castro, F. Ballesteros, A. Méndez, A. M. Tarquis

“…The laplacian pyramid is a well-known technique for image processing in which local operators of many scales, but identical shape, serve as the basis functions. …”
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Real-Time Batch Detection System for Defects in Highly Curved Spiral Cylindrical Coils by Qinghang Zhuo, Linghua Kong, Jishi Zheng, Zhigang Ding, Wenguang Li, Dingrong Yi, Guofu Lian

“…Secondly, a sub-pixel edge detection method based on image processing technology and the Canny algorithm is proposed to address the issue of difficulty in measuring the geometric dimensions of tungsten coils due to their high bending spiral structure. …”
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Reduced-Dimensional Capture of High-Dynamic Range Images with Compressive Sensing by Shundao Xie, Wenfang Wu, Rongjun Chen, Hong-Zhou Tan

“…Therefore, this paper proposes a method for reduced-dimensional capture of high dynamic range images with compressive sensing, which includes algorithms for front end (capturing) and back end (processing). …”
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