Article
Computer Science, Software Engineering
Ankit Garg, Anuj Kumar Singh
Summary: This paper presents an improved technique for image retargeting, which uses the gradient energy map generation method to safeguard the prominent regions of the image. The efficiency of the technique is validated through objective and subjective image quality assessment.
Article
Computer Science, Information Systems
Ankit Garg, Anand Nayyar, Anuj Kumar Singh
Summary: This paper proposes an improved seam carving technique to overcome the limitations of traditional techniques by restricting the intersection of optimal seam points on line structures. Through subjective and objective evaluations, the effectiveness and high similarity of the proposed technique have been demonstrated.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Kan Huang, Chunwei Tian, Zhijing Xu, Nannan Li, Jerry Chun-Wei Lin
Summary: This paper proposes a Motion Context guided Edge-preserving network (MCE-Net) model for video salient object detection. MCE-Net can generate temporally consistent salient edges and refine the salient object regions completely and uniformly. Experimental results demonstrate the superior performance of the proposed method on five widely-used benchmarks.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Sanping Zhou, Jinjun Wang, Le Wang, Jimuyang Zhang, Fei Wang, Dong Huang, Nanning Zheng
Summary: Salient object detection has seen rapid development with the rise of Deep Neural Networks, with HIRN proposed in this paper as a novel and effective approach to preserve edge structures and improve accuracy in detection.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Computer Science, Hardware & Architecture
Seyedeh Bahereh Hassanpour, Ahmad Khonsari, Masoumeh Moradian, Seyed Pooya Shariatpanahi
Summary: Edge caching reduces access delay but increases leakage probability. The study proposes a chunk-based joint probabilistic caching approach to mislead eavesdropping adversaries and optimize cache placements. The proposed scalable approach outperforms existing methods in terms of privacy and communication cost.
Article
Computer Science, Information Systems
Ankit Garg, Anuj Kumar Singh
Summary: This paper introduces the seam diversion-based image retargeting (SDIR) algorithm and analyzes its performance through two experiments. Experiment 1 analyzes the impact of different edge detection operators on the algorithm, while Experiment 2 evaluates the performance based on the visual quality and quality of importance maps. The results show that the SDIR algorithm performs well in minimizing structural deformations on prominent objects.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Mathematics, Applied
Felipe Uribe, Yiqiu Dong, Per Christian Hansen
Summary: This paper investigates the application of the shrinkage horseshoe prior in edge-preserving settings and introduces its formulation. A Gibbs sampling framework is used to solve the hierarchical formulation of the Bayesian inverse problem, with one conditional distribution being high-dimensional Gaussian and the rest derived in closed form using a scale mixture representation of the heavy-tailed hyperpriors. Applications in imaging science demonstrate that our computational procedure is able to compute sharp edge-preserving posterior point estimates with reduced uncertainty.
SIAM JOURNAL ON SCIENTIFIC COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Yu Wang, Shuxiao Li
Summary: Co-salient object detection aims to detect common objects in a group of relevant images by leveraging spatial similarity, highlighting common objects while suppressing others and the background. This paper introduces a novel and effective Similarity Activation Module (SAM), as well as Edge Extraction Module (EEM) and Feature Fusion Module (FFM) that can be easily applied to existing methods.
PATTERN RECOGNITION LETTERS
(2022)
Article
Engineering, Electrical & Electronic
Ismail Hababeh, Lina R. Hammad, Mohammad I. Daoud, Mahasen S. Al-Najar
Summary: An efficient adaptive ultrasound image filter is proposed to reduce ultrasound speckle while maintaining the edge cues in the image. The filtering method adapts different window sizes and bandwidths based on the edge map and image radiation. Its performance is compared with eight existing image filtering methods, and the results show its potential to achieve effective speckle suppression in ultrasound images.
INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY
(2023)
Article
Computer Science, Software Engineering
Dingkun Zhu, Weiming Wang, Xue Xue, Haoran Xie, Gary Cheng, Fu Lee Wang
Summary: Image smoothing is an important operation to enhance low-frequency structural parts and reduce noise and high-frequency textures in an image. This paper proposes a structure-preserving image smoothing network, which combines paired unsmoothed/smoothed images and meaningful edge information to improve performance. The network is trained using contrastive learning on the extended BSD500 dataset and utilizes an edge-aware total variation loss function for structure preservation. Experimental results show that our network outperforms state-of-the-art image smoothing methods in terms of SSIM and PSNR.
Article
Computer Science, Artificial Intelligence
Xing Zhao, Haoran Liang, Ronghua Liang
Summary: Multilevel feature fusion is crucial in salient object detection. This article proposes a global position embedding attention (GPEA) module, an object refine attention (ORA) module, and a pixel value (PV) loss to improve the effectiveness of salient object detection.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Optics
Rong Zou, Wenjie Dai, Shenghe Bai, Senlin Mu
Summary: In this study, a novel method for super-resolution of LF images is proposed, which uses both the macro pixel image (MacPI) and the sub-aperture image (SAI) of the LF. The edge map is introduced into the condition network to maintain the edge features of the image. A feature affine-transformation module is designed to guide the features extracted from the SAIs. The super-resolution LF image is recovered using an up-sampling network.
OPTICS AND LASERS IN ENGINEERING
(2024)
Article
Engineering, Electrical & Electronic
Indranil Misra, Mukesh Kumar Rohil, S. Manthira Moorthi, Debajyoti Dhar
Summary: Remote Sensing Image Fusion is achieved by merging panchromatic and multispectral images to create a high resolution multispectral image. Existing techniques lack in preserving the spectral characteristics of the multispectral image in the fused output. The proposed Spectra Preserving Radiance Image Fusion Technique (SPRINT) addresses this limitation through holistic deep edges and terrain guidance to maintain spectral fidelity. Evaluation of SPRINT using various datasets shows superior fusion performance compared to state-of-the-art methods, with close agreement in vegetation index and surface reflectance measurements.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2023)
Article
Engineering, Electrical & Electronic
Jun Lin, Jin Ma, Jianguo Zhu
Summary: Accurate estimation of residential solar photovoltaic generation is crucial for power distribution and demand response programs. A novel method using a federated learning-based Bayesian neural network (FL-BNN) is proposed to disaggregate BTM solar generation at the community level, preserving utility privacy. The effectiveness of the method is validated on a publicly available dataset.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Genetics & Heredity
Yu-Jyun Huang, Rajarshi Mukherjee, Chuhsing Kate Hsiao
Summary: This study proposes a method that combines Bayesian Markov random field with conditional autoregressive model to simultaneously handle the uncertainty of edge existence and the relative strength of edges in gene regulatory networks. The proposed approach can also prioritize the importance of edges based on their strength. Performance evaluation using simulations and a glioblastoma cancer study shows that the proposed method performs stably and may provide novel insights into biological structures.
FRONTIERS IN GENETICS
(2022)
Article
Engineering, Electrical & Electronic
Xueyu Han, Ishtiaq Rasool Khan, Susanto Rahardja
Summary: This paper proposes a clustering-based TMO method by embedding human visual system models to adapt to different HDR scenes. The method reduces computational complexity using a hierarchical scheme for clustering and enhances local contrast by superimposing details and controlling color saturation by limiting the adaptive saturation parameter. Experimental results show that the proposed method achieves improvements in generating high quality tone-mapped images compared to competing methods.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2024)
Article
Engineering, Electrical & Electronic
Zuopeng Zhao, Tianci Zheng, Kai Hao, Junjie Xu, Shuya Cui, Xiaofeng Liu, Guangming Zhao, Jie Zhou, Chen He
Summary: The research team developed a handheld phone detection network called YOLO-PAI, which successfully achieved real-time detection and underwent testing under various conditions. Experimental results show that YOLO-PAI reduces network structure parameters and computational costs while maintaining accuracy, outperforming other popular networks in terms of speed and accuracy.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2024)
Article
Engineering, Electrical & Electronic
Vivek Sharma, Ashish Kumar Tripathi, Purva Daga, M. Nidhi, Himanshu Mittal
Summary: In this study, a novel ClGan method is proposed for automated plant disease detection. The method reduces the number of parameters and addresses the issues of vanishing gradients, training instability, and non-convergence by using an encoder-decoder network. Additionally, an improved loss function is introduced to stabilize the learning process and optimize weights effectively. Furthermore, a new plant leaf classification method called ClGanNet is introduced, achieving 99.97% training accuracy and 99.04% testing accuracy using the least number of parameters.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2024)
Article
Engineering, Electrical & Electronic
Seongeun Kim, Chang-Ock Lee
Summary: This article introduces a method for segmenting individual teeth in human teeth images by using deep neural networks to obtain pseudo edge-regions and applying active contour models for segmentation.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2024)