In recent years, no-reference/blind image quality assessment (NR-IQA), as a fundamental but challenging research problem, has been attracting significant attention in the field of digital processing. NR-IQA aims to build computational model quantitatively predict subjective from distorted itself without any reference image. Although great efforts have employed develop various algorithms, due its intrinsic difficulty, issues are still and remain largely unexplored date. this paper, we...

Point cloud registration plays a central role in various applications, such as 3D scene reconstruction, preservation of cultural heritage and deformation monitoring. The point data are usually huge. Processing huge is very time-consuming, so fast accurate method crucial. However, the existing methods still have high computation complexity or low accuracy. To address this issue, we develop for terrestrial clouds. projects clouds onto horizontal plane. Therefore, our processes 2D space,...

The linear elastic models of soft tissue are widely used in virtual-reality-based surgery simulation due to their computational efficiency; however, it is well known that these only a coarse approximation the real biological tissue. To achieve realistic simulation, deformable model should incorporate many other properties such as nonlinearity, anisotropy, and viscoelasticity. Among properties, viscoelasticity very important one, directly determines behaviors when cut, deformed, or torn. In...

A new hybrid soft tissue model, which is mainly based on the mass-spring model (MSM) and 3-D finite strain nonlinear anisotropic elasticity theory, presented for visio-haptic simulations, such as surgery simulators. One significant difference from conventional MSMs that internal forces among mass nodes are derived within framework of continuum mechanics. As a result, much more realistic in sense it incorporates typical biological properties behaviors living nonlinearity, anisotropy,...

Denoising convolutional neural networks (DnCNNs), initially developed for Gaussian noise removal, are powerful nonlinear mapping models in image processing. After changes training data, they can be used suppression of random-valued impulse (RVIN) with excellent results. To achieve favorable denoising performance, however, it is necessary to have an accurate perception the ratio so that most suitable DnCNN chosen denoising. Thus, this model severely limited flexibility. address problem, we...

Aiming to dynamic modeling of a three-link manipulator subjected motion constraints, novel explicit approach the dynamical equations based on Udwadia-Kalaba (UK) theory is established. The constraints can be regarded as external system. However, it not easy obtain for constrained systems. For multibody system subjecting common introduce Lagrange multipliers, but obtaining an equation using traditional multipliers difficult. In order such more simply, are handled UK equation. Compared with...

High-resolution remote sensing (HRRS) images contain abundant and complex visual contents. It is very important to extract powerful features represent the contents of HRRS in image retrieval. This letter proposes a region-based cascade pooling (RBCP) method aggregate convolutional from both pre-trained fine-tuned neural networks (CNNs). The RBCP adopts small regions, first uses max-pooling on feature maps last layer, then employs average-pooling max-pooled maps. Furthermore, map size related...

In this paper, a new intuitionistic fuzzy model for images based on the HSV color histogram is proposed. The image can be treated as an Attanassov’s set (IFS) with model. A and simple calculation of similarity measurement called IFSL1 L1 presented. Unlike general measure that consider only membership degree, takes into account nonmembership degree hesitation these have been found to highly useful in dealing vagueness. used content-based retrieval (CBIR).With IFSL1, carried out more rapidly...

In the present work, majority of implemented virtual surgery simulation systems have been based on either a mesh or meshless strategy with regard to soft tissue modelling. To take full advantage and models, novel coupled cutting model is proposed. Specifically, reconstructed consists two essential components. One associated surface that convenient for rendering other internal point elements used calculate force feedback during cutting. combine components in seamless way, points are...

Aiming at partitioning an image into homogeneous and meaningful regions, automatic segmentation is a fundamental but challenging problem in computer vision.It well known that Fuzzy c-means (FCM) algorithm one of the most popular methods for segmentation.However, FCM-based must be manually estimated to determine cluster number by users.In this paper, we propose novel adaptive fuzzy (CNAFCM) automatically grouping pixels different regions when not beforehand.We utilize Grey Level Co-occurrence...

Image denoising poses a significant challenge in computer vision due to the high-level visual task’s dependency on image quality. Several advanced models have been proposed recent decades. Recently, deep prior (DIP), using particular network structure and noisy achieve denoising, has provided novel method. However, performance of DIP model still lags behind that mainstream models. To improve model, we propose TripleDIP with internal external mixed images priors for denoising. The comprises...

Point cloud registration is a fundamental problem in many applications. The point based on local shape descriptor has been widely researched. In order to further improve the performance of registration, novel method proposed this paper. First, binary designed establish correspondences between two clouds. high descriptiveness. Thus, more correct are established. Then, 3D transformation estimation technique developed, which multiple constraints used accelerate computation. When randomly...

Over the last decade, supervised denoising models, trained on extensive datasets, have exhibited remarkable performance in image denoising, owing to their superior effects. However, these models exhibit limited flexibility and manifest varying degrees of degradation noise reduction capability when applied practical scenarios, particularly distribution a given noisy deviates from that training images. To tackle this problem, we put forward two-stage model is actualized by attaching an...

Over the past decade, significant advancements have been made in low-light image enhancement (LLIE) methods due to robust capabilities of deep learning non-linear mapping, feature extraction, and representation. However, pursuit a universally superior method that consistently outperforms others across diverse scenarios remains challenging. This challenge primarily arises from inherent data bias learning-based approaches, stemming disparities statistical distributions between training testing...

Compared to supervised denoising models based on deep learning, the unsupervised Deep Image Prior (DIP) approach offers greater flexibility and practicality by operating solely with given noisy image. However, random initialization of network input parameters in DIP leads a slow convergence during iterative training, affecting execution efficiency heavily. To address this issue, we propose Masked-Pre-training-Based Fast (MPFDIP) Denoising Model paper. We enhance classical Restormer framework...

In this letter, a novel multiple image-based Gaussian noise level estimation (NLE) algorithm for natural images by jointly exploiting the level-aware feature extraction and local means (LM) techniques was proposed. We employed some efficient powerful features in form of vector to characterize levels across image contents. Based on this, we adopted LM scheme estimate an be estimated comparing similar preconstructed sample database. had verified accuracy efficiency proposed NLE large from...

The main drawback of the phase congruency feature employed in similarity index (FSIM) image quality assessment (IQA) algorithm is its low computational efficiency. In this paper, a novel fast (FFSIM) for proposed. Based on fact that human visual system (HVS) responds to brightness stimulus mainly complying with Weber's law, proposed FFSIM only performs spatial filtering quickly calculate contrast between current pixel and background, which used compute Weber salience weighting coefficient...