Signal Processing-Image Communication最新文献

{"title":"An improved Siamese network-based tracking method for UAV video with salt-and-pepper noise","authors":"Xin Lu ,&nbsp;Yong Wang ,&nbsp;Fusheng Li","doi":"10.1016/j.image.2025.117366","DOIUrl":"10.1016/j.image.2025.117366","url":null,"abstract":"<div><div>In practical application of unmanned aerial vehicle (UAV) monitoring system, the video in visual tracking system inevitably introduces salt-and-pepper (s&amp;p) noise because of the interference from external environment. At this time, it could degrade the performance or lead to tracking failure. However, most existing tracking algorithms focus on the improvement of accuracy and robustness while ignore the video quality enhancement. To this end, this paper proposes a Siamese network-based tracker together with a denoising module to reduce the effect of s&amp;p noise. The proposed tracker firstly adds a simpler version of adaptive median layer into feedforward denoising convolutional neural network to form a video quality enhancer to achieve the noise suppression. Then by means of Siamese network, the tracker extracts the features of preprocessed detection frame and template frame, and the region proposal network (RPN) is utilized to generate the foreground candidate box and its position. Thus, the proposed tracker can maintain the stability and effectiveness of tracking under the influences of the s&amp;p noise. In addition, we construct a noisy DTB70 dataset with genetated noise for experimental validation. Experimental results show that the proposed method can track the target effectively at different noise levels. It is worth mentioning that our proposed method reports promising results on s&amp;p noise even with high levels.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117366"},"PeriodicalIF":3.4,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144279799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ZERRIN-Net: Adaptive low-light image enhancement using Retinex decomposition and noise extraction","authors":"Wenchao Li ,&nbsp;Shuyuan Wen ,&nbsp;Jinhao Zhu ,&nbsp;Qiaofeng Ou ,&nbsp;Yanchun Guo ,&nbsp;Jiabao Chen ,&nbsp;Bangshu Xiong","doi":"10.1016/j.image.2025.117345","DOIUrl":"10.1016/j.image.2025.117345","url":null,"abstract":"<div><div>Low-light image enhancement aims at correcting the exposure of images taken under underexposed conditions while removing image noise and restoring image details. Most of the previous low-light image enhancement algorithms used hand-made a priori denoising in the corrected component; however, due to the large amount of detail information of the image contained in the corrected component and the presence of some pseudo-noise, the final enhancement results obtained by these solutions do not have the original noise removed, and the image details appear blurred. To solve the above problems, we propose ZERRIN-Net, a zero-shot low-light enhancement method based on Retinex decomposition. First of all, we first design the original noise extraction network N-Net, which can adaptively extract the original noise of low-light images without losing the detailed information of the images. In addition, we propose the decomposition network RI-Net, which is based on the Retinex principle and utilizes a simple self-supervised mechanism to help decompose a low-light image into a reflection component and a light component. In this paper, we conduct extensive experiments on numerous datasets as well as advanced vision tasks such as face detection, target recognition, and instance segmentation. The experimental results show that the performance of our method is competitive with current state-of-the-art methods. The code is available at: <span><span>https://github.com/liwenchao0615/ZERRINNet</span><svg><path></path></svg></span></div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117345"},"PeriodicalIF":3.4,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147613","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiple-image encryption algorithm based on S-boxes and DNA sequences","authors":"Muhammad Umair Safdar ,&nbsp;Tariq Shah ,&nbsp;Asif Ali","doi":"10.1016/j.image.2025.117353","DOIUrl":"10.1016/j.image.2025.117353","url":null,"abstract":"<div><div>Image encryption is crucial for safeguarding sensitive visual data; however, traditional methods often encounter challenges regarding efficiency and adaptability to the unique characteristics of images. This research is motivated by the potential of ring-based algebraic structures to develop lightweight, secure, and efficient encryption schemes specifically designed for image data. The article presents a novel approach to image encryption in cryptography using a local ring algebraic structure. The proposed method involves encrypting multiple images by constructing substitution boxes from subsets, which are not subgroups but have identity and invertibility axioms. The challenge of using subsets for encryption purposes is addressed by taking unit elements of the ring, picking a subgroup, and splitting it into two subsets. The substitution box is generated by one of the subsets and used for the substitution process, while the other subset is mapped to the Galois field. It constructs the substitution box and is used for diffusion. A DNA sequence is applied to the red, green, and blue channels of the image, and a key is generated by hashing the image and using a subset of the subgroup of units of the ring. Finally, all channels are XORed with the key. The performance of the proposed scheme is evaluated using different analyses, and it is found that the scheme outperforms existing approaches. This approach presents a promising solution for image encryption in cryptography.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117353"},"PeriodicalIF":3.4,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144177675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Motion-blurred image restoration in haze weather based on the color line model","authors":"Jiamin Li,&nbsp;Hongping Hu,&nbsp;Yanping Bai","doi":"10.1016/j.image.2025.117352","DOIUrl":"10.1016/j.image.2025.117352","url":null,"abstract":"<div><div>Many dehazing algorithms had been developed for hazy images caused by industrial pollution and hazy weather. However, most of the dehazing algorithms only consider the restoration of images in static scenes and ignore the restoration of hazy images in dynamic scenes. Based on this, this paper proposed an image recovery algorithm based on the color line model for dynamic scenes under hazy weather. The algorithm was divided into two parts: To improve image contrast by image dehazing and to improve image clarity by deblurring the dynamic scene. Firstly, the watershed algorithm was used to divide the image into foreground and background; Secondly, the color line model was used to restore the motion blur of the foreground image; At the same time, the color line model was adopted to dehazing the hazy background image; And finally, the foreground image and the background image were fused. The experimental results were shown that compared with other mainstream dehazing and deblurring algorithms, the recovered image of this paper's algorithm performs well in terms of both color assurance and texture details, and has better evaluation indexes.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117352"},"PeriodicalIF":3.4,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hyperspectral mixed noise removal using nonconvex low-rank and total generalized variation","authors":"Xinwu Liu","doi":"10.1016/j.image.2025.117344","DOIUrl":"10.1016/j.image.2025.117344","url":null,"abstract":"<div><div>To better preserve the structural features while removing the mixed noise in hyperspectral image (HSI), this paper presents a novel HSI denoising method based on nonconvex low-rank (NLR) and total generalized variation (TGV) minimization. The proposed NLRTGV solver closely incorporates the advantages of TGV regularization, nonconvex nuclear norm, and <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>-norm. More specifically, the TGV regularizer, which maintains the spatial structure features, is adopted to eliminate Gaussian noise and prevent the staircase artifacts. The usage of nonconvex penalty is to explore the spectral low-rank properties, which contributes to suppress the sparse noise and preserve the major data components. Besides, we further employ the <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>-norm regularization to detect the sparse noise that includes impulse noise, deadlines and stripes. Computationally, by combining the iteratively reweighted <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span> algorithm, singular value shrinkage method and primal-dual framework, we construct in detail a modified alternating direction method of multipliers to solve the resulting optimization problem. Finally, as evidently demonstrated in both simulated and real-world HSI datasets experiments, our proposed approach shows the outstanding denoising performance in terms of mixed noise removal and detail features preservation, over the existing state-of-the-art competitors.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117344"},"PeriodicalIF":3.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144147612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Signal processing for haptic surface modeling: A review","authors":"Antonio Luigi Stefani ,&nbsp;Niccolò Bisagno ,&nbsp;Andrea Rosani ,&nbsp;Nicola Conci ,&nbsp;Francesco De Natale","doi":"10.1016/j.image.2025.117338","DOIUrl":"10.1016/j.image.2025.117338","url":null,"abstract":"<div><div>Haptic feedback has been integrated into Virtual and Augmented Reality, complementing acoustic and visual information and contributing to an all-round immersive experience in multiple fields, spanning from the medical domain to entertainment and gaming. Haptic technologies involve complex cross-disciplinary research that encompasses sensing, data representation, interactive rendering, perception, and quality of experience. The standard processing pipeline, consists of (I) sensing physical features in the real world using a transducer, (II) modeling and storing the collected information in some digital format, (III) communicating the information, and finally, (IV) rendering the haptic information through appropriate devices, thus producing a user experience (V) perceptually close to the original physical world. Among these areas, sensing, rendering and perception have been deeply investigated and are the subject of different comprehensive surveys available in the literature. Differently, research dealing with haptic surface modeling and data representation still lacks a comprehensive dissection. In this work, we aim at providing an overview on modeling and representation of haptic surfaces from a signal processing perspective, covering the aspects that lie in between haptic information acquisition on one side and rendering and perception on the other side. We analyze, categorize, and compare research papers that address the haptic surface modeling and data representation, pointing out existing gaps and possible research directions.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117338"},"PeriodicalIF":3.4,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144131260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Driver distraction detection based on adaptive tiny targets and lightweight networks","authors":"Shuangshuang Gu ,&nbsp;Bin Wen ,&nbsp;Shiyao Chen ,&nbsp;Yuanyuan Li ,&nbsp;Guanqiu Qi ,&nbsp;Linhong Shuai ,&nbsp;Zhiqin Zhu","doi":"10.1016/j.image.2025.117342","DOIUrl":"10.1016/j.image.2025.117342","url":null,"abstract":"<div><div>Driver distraction detection is critical to reducing road traffic accidents and increasing the efficiency of advanced driver assistance systems. Real-time lightweight models are especially important for in-vehicle devices with limited computing resources. However, most existing methods focus on designing lighter network architectures and ignore the performance loss when detecting tiny targets. In order to realize the collaborative optimization of tiny target detection accuracy and network lightweight, a driver distraction detection method ATD<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>Net based on adaptive tiny target detection and lightweight networks is proposed. This method aims to reduce model complexity while fully capturing target features for accurate detection. ATD<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>Net consists of three core modules, Channel Reconstruction Perception Module (CRPM), Dynamic Spatial Self-locking Module (DSSM) and Structural Feedback Optimization Module (SFOM). CRPM reconfigures channels and reconstructs them into batch dimensions, uses parallel strategies to perceive interactive features between channels, and significantly enhances feature extraction capabilities. DSSM adopts dynamic locking and adaptive spatial selection mechanisms to capture multi-scale features while injecting adaptive spatial information. It effectively aggregates instance features and reduces the interference of conflicting information and background information, thereby improving the detection ability of tiny targets. SFOM uses dependency trees to model inter-layer relationships and integrate coupling parameters into groupings. It uses a sparse strategy to remove unimportant parameters, achieving lightweight modeling while balancing accuracy and speed. Experimental results show that ATD<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>Net is superior to the latest methods in driver distraction detection, showing excellent performance and good application prospects.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117342"},"PeriodicalIF":3.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144090347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sparse modeling for image inpainting: A multi-scale morphological patch-based k-SVD and group-based PCA","authors":"Amit Soni Arya,&nbsp;Susanta Mukhopadhyay","doi":"10.1016/j.image.2025.117341","DOIUrl":"10.1016/j.image.2025.117341","url":null,"abstract":"<div><div>Image inpainting, a crucial task in image restoration, aims to reconstruct highly degraded images with missing pixels while preserving structural and textural integrity. Traditional patch-based and group-based sparse representation methods often struggle with visual artifacts and over-smoothing, limiting their effectiveness. To address these challenges, we propose a novel multi-scale morphological patch-based and group-based sparse representation learning approach for image inpainting. Our method enhances image inpainting by integrating morphological patch-based sparse representation (M-PSR) learning using k-singular value decomposition (k-SVD) and group-based sparse representation using principal component analysis (PCA) to construct adaptive dictionaries for improved reconstruction accuracy. Additionally, we employ the alternating direction method of multipliers (ADMM) to optimize the integration of morphological patch and group based sparse representations, enhancing restoration quality. Extensive experiments on various degraded images demonstrate that our approach outperforms state-of-the-art methods in terms of the peak signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM). The proposed method effectively reconstructs images corrupted by missing pixels, scratches, and text inlays, achieving superior structural coherence and perceptual quality. This work contributes a robust and efficient solution for image inpainting, offering significant advances in sparse modeling and morphological image processing.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117341"},"PeriodicalIF":3.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An algorithm for voxelised solids representation using chain codes","authors":"Blaž Repnik ,&nbsp;Libor Váša ,&nbsp;Borut Žalik","doi":"10.1016/j.image.2025.117340","DOIUrl":"10.1016/j.image.2025.117340","url":null,"abstract":"<div><div>The paper introduces a new method to describe the surfaces of voxelised solids. It operates in three stages: a hierarchical linked list of chain code sequences is created first; the linked lists are pruned; and, finally, the content of the data structure is stored. The method uses chain codes from either a three- or nine-symbols alphabet. In the first case, two chain code symbols are needed to access the next face, while, in the second case, this is done by one symbol. The pair of chain codes from the three-symbols alphabet, or the individual symbol from the nine-symbols alphabet are considered as tokens. The sets of tokens are, in both cases, extended by two tokens, indicating the beginning and ending of the list. The method processes solids of any shape, including those containing holes, cavities, or multiple components existing in the same voxel space. Edge-connectivity is permitted. The method was compared against the method proposed by Lemus et al., which is designed for solids without holes. Although supporting a broader set of voxelised solids, the proposed method generates sequences of tokens that are, on average, up to 10% shorter. Since the information entropy of the sequences of tokens produced by the proposed method is also smaller, the obtained sequences are more compressible, as confirmed by applying <strong>gzip</strong> and <strong>bzip2</strong> data compressors.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117340"},"PeriodicalIF":3.4,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144125382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Facial expression transformation for anime-style image based on decoder control and attention mask","authors":"Xinhao Rao ,&nbsp;Weidong Min ,&nbsp;Ziyang Deng ,&nbsp;Mengxue Liu","doi":"10.1016/j.image.2025.117343","DOIUrl":"10.1016/j.image.2025.117343","url":null,"abstract":"<div><div>Human facial expression transformation has been extensively studied using Generative Adversarial Networks (GANs) recently. GANs have also shown successful attempts in transforming anime-style images. However, current methods for anime pictures fail to refine the expression control efficiently, leading to control effects weaker than expected. Moreover, it remains challenging to maintain the original anime face identity information while transforming. To address these issues, we propose an expression transformation method for anime-style images. In order to enhance the control effect of discrete emoticon tags, a mapping network is proposed to map them to high-dimensional control information, which is then injected into the network multiple times during transformation. Additionally, for better maintaining the anime face identity information while transforming, an integrated attention mask mechanism is introduced to enable the network's expression control to focus on the expression-related features, while avoiding affecting the unrelated features. Finally, we conduct a large number of experiments to verify the validity of the proposed method, and both quantitative and qualitative evaluations are carried out. The results demonstrate the superiority of our proposed method compared to existing methods based on multi-domain image-to-image translation.</div></div>","PeriodicalId":49521,"journal":{"name":"Signal Processing-Image Communication","volume":"138 ","pages":"Article 117343"},"PeriodicalIF":3.4,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}