RGB-guided hyperspectral image super-resolution with deep progressive learning

Due to hardware limitations,existing hyperspectral(HS)camera often suffer from low spatial/temporal resolution.Recently,it has been prevalent to super-resolve a low reso-lution(LR)HS image into a high resolution(HR)HS image with a HR RGB(or mul-tispectral)image guidance.Previous approaches for this guided super-resolution task often model the intrinsic characteristic of the desired HR HS image using hand-crafted priors.Recently,researchers pay more attention to deep learning methods with direct supervised or unsupervised learning,which exploit deep prior only from training dataset or testing data.In this article,an efficient convolutional neural network-based method is presented to progressively super-resolve HS image with RGB image guidance.Specif-ically,a progressive HS image super-resolution network is proposed,which progressively super-resolve the LR HS image with pixel shuffled HR RGB image guidance.Then,the super-resolution network is progressively trained with supervised pre-training and un-supervised adaption,where supervised pre-training learns the general prior on training data and unsupervised adaptation generalises the general prior to specific prior for variant testing scenes.The proposed method can effectively exploit prior from training dataset and testing HS and RGB images with spectral-spatial constraint.It has a good general-isation capability,especially for blind HS image super-resolution.Comprehensive experimental results show that the proposed deep progressive learning method out-performs the existing state-of-the-art methods for HS image super-resolution in non-blind and blind cases.

Precise region semantics-assisted GAN for pose-guided person image generation

Generating a realistic person's image from one source pose conditioned on another different target pose is a promising computer vision task.The previous mainstream methods mainly focus on exploring the transformation relationship between the keypoint-based source pose and the target pose,but rarely investigate the region-based human semantic information.Some current methods that adopt the parsing map neither consider the precise local pose-semantic matching issues nor the correspondence between two different poses.In this study,a Region Semantics-Assisted Generative Adversarial Network(RSA-GAN)is proposed for the pose-guided person image gen-eration task.In particular,a regional pose-guided semantic fusion module is first devel-oped to solve the imprecise match issue between the semantic parsing map from a certain source image and the corresponding keypoints in the source pose.To well align the style of the human in the source image with the target pose,a pose correspondence guided style injection module is designed to learn the correspondence between the source pose and the target pose.In addition,one gated depth-wise convolutional cross-attention based style integration module is proposed to distribute the well-aligned coarse style information together with the precisely matched pose-guided semantic information to-wards the target pose.The experimental results indicate that the proposed RSA-GAN achieves a 23%reduction in LPIPS compared to the method without using the seman-tic maps and a 6.9%reduction in FID for the method with semantic maps,respectively,and also shows higher realistic qualitative results.

CA IX-targeted Ag_(2)S quantum dots bioprobe for NIR-II imaging-guided hypoxia tumor chemo-photothermal therapy

Hypoxia is the common characteristic of almost all solid tumors,which prevents therapeutic drugs from reaching the tumors.Therefore,the development of new targeted agents for the accurate diagnosis of hypoxia tumors is widely concerned.As carbonic anhydrase IX(CA IX)is abundantly distributed on the hypoxia tumor cells,it is considered as a potential tumor biomarker.4-(2-Aminoethyl)benzenesulfonamide(ABS)as a CA IX inhibitor has inherent inhibitory activity and good targeting effect.In this study,Ag_(2)S quantum dots(QDs)were used as the carrier to prepare a novel diagnostic and therapeutic bioprobe(Ag_(2)S@polyethylene glycol(PEG)-ABS)through ligand exchange and amide condensation reaction.Ag_(2)S@PEG-ABS can selectively target tumors by surface-modified ABS and achieve accurate tumor imaging by the near infrared-II(NIR-II)fluorescence characteristics of Ag_(2)S QDs.PEG modification of Ag_(2)S QDs greatly improves its water solubility and stability,and therefore achieves high photothermal stability and high photothermal conversion efficiency(PCE)of 45.17%.Under laser irradiation,Ag_(2)S@PEG-ABS has powerful photothermal and inherent antitumor combinations on colon cancer cells(CT-26)in vitro.It also has been proved that Ag_(2)S@PEG-ABS can realize the effective treatment of hypoxia tumors in vivo and show good biocompatibility.Therefore,it is a new efficient integrated platform for the diagnosis and treatment of hypoxia tumors.

Two-view attention-guided convolutional neural network for mammographic image classification

Deep learning has been widely used in the field of mammographic image classification owing to its superiority in automatic feature extraction.However,general deep learning models cannot achieve very satisfactory classification results on mammographic images because these models are not specifically designed for mammographic images and do not take the specific traits of these images into account.To exploit the essential discriminant information of mammographic images,we propose a novel classification method based on a convolutional neural network.Specifically,the proposed method designs two branches to extract the discriminative features from mammographic images from the mediolateral oblique and craniocaudal(CC)mammographic views.The features extracted from the two-view mammographic images contain complementary information that enables breast cancer to be more easily distinguished.Moreover,the attention block is introduced to capture the channel-wise information by adjusting the weight of each feature map,which is beneficial to emphasising the important features of mammographic images.Furthermore,we add a penalty term based on the fuzzy cluster algorithm to the cross-entropy function,which improves the generalisation ability of the classification model by maximising the interclass distance and minimising the intraclass distance of the samples.The experimental results on The Digital database for Screening Mammography INbreast and MIAS mammography databases illustrate that the proposed method achieves the best classification performance and is more robust than the compared state-ofthe-art classification methods.

Past,present,and future perspectives of ultrasound-guided ablation of liver tumors:Where could artificial intelligence lead interventional oncology?

The first ablation procedures for small hepatocellular carcinomas were percutaneous ethanol injection under ultrasound(US)guidance.Later,radiofrequency ablation was shown to achieve larger coagulation areas than percutaneous ethanol injection and became the most used ablation technique worldwide.In the past decade,microwave ablation systems have achieved larger ablation areas than radiofrequency ablation,suggesting that the 3-cm barrier could be broken in the treatment of liver tumors.Likewise,US techniques to guide percutaneous ablation have seen important progress.Contrast-enhanced US(CEUS)can define and target the tumor better than US and can assess the size of the ablation area after the procedure,which allows immediate retreatment of the residual tumor foci.Furthermore,fusion imaging fuses real-time US images with computed tomography or magnetic resonance imaging with significant improvements in detecting and targeting lesions with low conspicuity on CEUS.Recently,software powered by artificial intelligence has been developed to allow three-dimensional segmentation and reconstruction of the anatomical structures,aiding in procedure planning,assessing ablation completeness,and targeting the residual viable foci with greater precision than CEUS.Hopefully,this could lead to the ablation of tumors up to 5-7 cm in size.

Unrolling a rain-guided detail recovery network for single-image deraining

Background Owing to the rapid development of deep networks, single-image deraining tasks have progressed significantly. Various architectures have been designed to recursively or directly remove rain, and most rain streaks can be removed using existing deraining methods. However, many of them cause detail loss, resulting in visual artifacts. Method To resolve this issue, we propose a novel unrolling rain-guided detail recovery network(URDRN) for single-image deraining based on the observation that the most degraded areas of a background image tend to be the most rain-corrupted regions. Furthermore, to address the problem that most existing deep-learningbased methods trivialize the observation model and simply learn end-to-end mapping, the proposed URDRN unrolls a single-image deraining task into two subproblems: rain extraction and detail recovery. Result Specifically, first, a context aggregation attention network is introduced to effectively extract rain streaks;thereafter, a rain attention map is generated as an indicator to guide the detail recovery process. For the detail recovery sub-network, with the guidance of the rain attention map, a simple encoder–decoder model is sufficient to recover the lost details.Experiments on several well-known benchmark datasets show that the proposed approach can achieve performance similar to those of other state-of-the-art methods.

Magnetic resonance imaging-guided percutaneous cryoablation of hepatocellular carcinoma in special regions

BACKGROUND: Local cryoablation guided by CT or ultrasound has been widely applied in the treatment of hepatocellular carcinoma. However, it is still difficult to apply this technique in certain regions such as the diaphragm dome, the first hepatic hilum, and regions adjacent to the gallbladder. This study aimed to evaluate the safety and efficacy of using magnetic resonance imaging (MRI)-guided percutaneous cryoablation as well as the effect of using an open MRI system in guiding and monitoring the treatment of hepatocellular carcinoma in these regions. METHODS: Cryoablation, guided by an open 0.35T MRI scanner and with the assistance of an MRI-compatible optical navigation system, was performed on 32 patients with hepatocellular carcinoma at the diaphragm dome, the first hepatic hilum, and regions adjacent to the gallbladder. Each patient had one or two tumors. The total number of tumors treated was 36. The tumor diameters ranged from 2.5 to 10.0 cm (mean 4.7+/-1.8 cm). The cryosurgical system was MRI-compatible and equipped with cryoprobes 1.47 mm in outside diameter. Under the guidance of MRI in combination with the optical navigation system, the cryoprobes were introduced percutaneously into a tumor at the planned targeting points while critical organs or tissues were avoided. Each cryoablation procedure included two freezing-thawing cycles, and MRI images were acquired dynamically to monitor the ablation of the tumor from time to time during the operation. In order to investigate the therapeutic effects of a cryoablation procedure, AFP measurements and liver-enhanced MRI or CT-enhanced scans were performed at regular times. RESULTS: MRI and optical navigation system-guided cryoablation procedures were successfully performed on all 32 patients (36 tumor sites) and no serious complications occurred. The follow-up period ranged from 5 to 12 months. The 6- and 12-month overall survival rates were 96.8% and 90.6%, respectively. According to the diagnosis of liver-enhanced MRI scans, 10 patients (31.3%) had complete ablation, 18 (56.3%) partial ablation (>80%), 3 (9.4%) stable disease (>50% ablation), and 1 (3.1%) progressive disease (a new tumor site in the liver). The overall efficacy was 87.5%. CONCLUSIONS: MR-guided percutaneous cryoablation using optical navigation is a safe and effective minimally invasive procedure for the treatment of hepatocellular carcinoma at certain special regions, which is difficult to treat with other imaging guidance approaches. With its unique and superb imaging functions, MRI plays an important role in the display, guidance, and monitoring of the cryoablation procedure in treating hepatocellular carcinoma at these special regions. Equipped with an MRI-compatible optical navigation system, MRI-guided therapy makes the cryoablation procedure more precise and safe.

Multifunctional magnetic nanoparticles for magnetic resonance image-guided photothermal therapy for cancer

Key advances in multifunctional magnetic nanoparticles （MNPs） for magnetic resonance （MR） image-guided pho- tothermal therapy of cancer are reviewed. We briefly outline the design and fabrication of such multifunctional MNPs. Bimodal image-guided photothermal therapies （MR/fluorescence and MR/ultrasound） are also discussed.

Fluorescent Silicon Nanorods-Based Nanotheranostic Agents for Multimodal Imaging-Guided Photothermal Therapy

The utilization of diagnosis to guide/aid therapy procedures has shown great prospects in the era of personalized medicine along with the recognition of tumor heterogeneity and complexity.Herein,a kind of multifunctional silicon-based nanostructure,i.e.,gold nanoparticles-decorated fluorescent silicon nanorods(Au@SiNRs),is fabricated and exploited for tumor-targeted multimodal imaging-guided photothermal therapy.In particular,the prepared Au@SiNRs feature high photothermal conversion efficiency(~43.9%)and strong photothermal stability(photothermal performance stays constant after five-cycle NIR laser irradiation),making them high-performance agents for simultaneously photoacoustic and infrared thermal imaging.The Au@SiNRs are readily modified with targeting peptide ligands,enabling an enhanced tumor accumulation with a high value of^8.74%ID g?1.Taking advantages of these unique merits,the Au@SiNRs are superbly suitable for specifically ablating tumors in vivo without appreciable toxicity under the guidance of multimodal imaging.Typically,all the mice treated with the Au@SiNRs remain alive,and no distinct tumor recurrence is observed during 60-day investigation.

Dendritic Learning-Incorporated Vision Transformer for Image Recognition

Dear Editor,This letter proposes to integrate dendritic learnable network architecture with Vision Transformer to improve the accuracy of image recognition.In this study,based on the theory of dendritic neurons in neuroscience,we design a network that is more practical for engineering to classify visual features.Based on this,we propose a dendritic learning-incorporated vision Transformer(DVT),which out-performs other state-of-the-art methods on three image recognition benchmarks.

The Soft X-ray Imager(SXI)on the SMILE Mission

The Soft X-ray Imager(SXI)is part of the scientific payload of the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.SMILE is a joint science mission between the European Space Agency(ESA)and the Chinese Academy of Sciences(CAS)and is due for launch in 2025.SXI is a compact X-ray telescope with a wide field-of-view(FOV)capable of encompassing large portions of Earth’s magnetosphere from the vantage point of the SMILE orbit.SXI is sensitive to the soft X-rays produced by the Solar Wind Charge eXchange(SWCX)process produced when heavy ions of solar wind origin interact with neutral particles in Earth’s exosphere.SWCX provides a mechanism for boundary detection within the magnetosphere,such as the position of Earth’s magnetopause,because the solar wind heavy ions have a very low density in regions of closed magnetic field lines.The sensitivity of the SXI is such that it can potentially track movements of the magnetopause on timescales of a few minutes and the orbit of SMILE will enable such movements to be tracked for segments lasting many hours.SXI is led by the University of Leicester in the United Kingdom(UK)with collaborating organisations on hardware,software and science support within the UK,Europe,China and the United States.

Background removal from global auroral images:Data-driven dayglow modeling

Global images of auroras obtained by cameras on spacecraft are a key tool for studying the near-Earth environment.However,the cameras are sensitive not only to auroral emissions produced by precipitating particles,but also to dayglow emissions produced by photoelectrons induced by sunlight.Nightglow emissions and scattered sunlight can contribute to the background signal.To fully utilize such images in space science,background contamination must be removed to isolate the auroral signal.Here we outline a data-driven approach to modeling the background intensity in multiple images by formulating linear inverse problems based on B-splines and spherical harmonics.The approach is robust,flexible,and iteratively deselects outliers,such as auroral emissions.The final model is smooth across the terminator and accounts for slow temporal variations and large-scale asymmetries in the dayglow.We demonstrate the model by using the three far ultraviolet cameras on the Imager for Magnetopause-to-Aurora Global Exploration(IMAGE)mission.The method can be applied to historical missions and is relevant for upcoming missions,such as the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)mission.

Portal hypertension: Imaging of portosystemic collateral pathways and associated image-guided therapy

Portal hypertension is a common clinical syndrome, defined by a pathologic increase in the portal venous pressure. Increased resistance to portal blood flow, the primary factor in the pathophysiology of portal hypertension, is in part due to morphological changes occurring in chronic liver diseases. This results in rerouting of blood flow away from the liver through collateral pathways to low-pressure systemic veins. Through a variety of computed tomographic, sonographic, magnetic resonance imaging and angiographic examples, this article discusses the appearances and prevalence of both common and less common portosystemic collateral channels in the thorax and abdomen. A brief overview of established interventional radiologic techniques for treatment of portal hypertension will also be provided. Awareness of the various imaging manifestations of portal hypertension can be helpful for assessing overall prognosis and planning proper management.

Two-photon live imaging of direct glia-to-neuron conversion in the mouse cortex

Over the past decade,a growing number of studies have reported transcription factor-based in situ reprogramming that can directly conve rt endogenous glial cells into functional neurons as an alternative approach for n euro regeneration in the adult mammalian central ne rvous system.Howeve r,many questions remain regarding how a terminally differentiated glial cell can transform into a delicate neuron that forms part of the intricate brain circuitry.In addition,concerns have recently been raised around the absence of astrocyte-to-neuron conversion in astrocytic lineage-tra cing mice.In this study,we employed repetitive two-photon imaging to continuously capture the in situ astrocyte-to-neuron conversion process following ecto pic expression of the neural transcription factor NeuroD1 in both prolife rating reactive astrocytes and lineage-tra ced astrocytes in the mouse cortex.Time-lapse imaging over several wee ks revealed the ste p-by-step transition from a typical astrocyte with numero us short,tapered branches to a typical neuro n with a few long neurites and dynamic growth cones that actively explored the local environment.In addition,these lineage-converting cells were able to migrate ra dially or to ngentially to relocate to suitable positions.Furthermore,two-photon Ca2+imaging and patch-clamp recordings confirmed that the newly generated neuro ns exhibited synchronous calcium signals,repetitive action potentials,and spontaneous synaptic responses,suggesting that they had made functional synaptic connections within local neural circuits.In conclusion,we directly visualized the step-by-step lineage conversion process from astrocytes to functional neurons in vivo and unambiguously demonstrated that adult mammalian brains are highly plastic with respect to their potential for neuro regeneration and neural circuit reconstruction.

Using restored two-dimensional X-ray images to reconstruct the three-dimensional magnetopause

Astronomical imaging technologies are basic tools for the exploration of the universe,providing basic data for the research of astronomy and space physics.The Soft X-ray Imager(SXI)carried by the Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)aims to capture two-dimensional(2-D)images of the Earth’s magnetosheath by using soft X-ray imaging.However,the observed 2-D images are affected by many noise factors,destroying the contained information,which is not conducive to the subsequent reconstruction of the three-dimensional(3-D)structure of the magnetopause.The analysis of SXI-simulated observation images shows that such damage cannot be evaluated with traditional restoration models.This makes it difficult to establish the mapping relationship between SXIsimulated observation images and target images by using mathematical models.We propose an image restoration algorithm for SXIsimulated observation images that can recover large-scale structure information on the magnetosphere.The idea is to train a patch estimator by selecting noise–clean patch pairs with the same distribution through the Classification–Expectation Maximization algorithm to achieve the restoration estimation of the SXI-simulated observation image,whose mapping relationship with the target image is established by the patch estimator.The Classification–Expectation Maximization algorithm is used to select multiple patch clusters with the same distribution and then train different patch estimators so as to improve the accuracy of the estimator.Experimental results showed that our image restoration algorithm is superior to other classical image restoration algorithms in the SXI-simulated observation image restoration task,according to the peak signal-to-noise ratio and structural similarity.The restoration results of SXI-simulated observation images are used in the tangent fitting approach and the computed tomography approach toward magnetospheric reconstruction techniques,significantly improving the reconstruction results.Hence,the proposed technology may be feasible for processing SXI-simulated observation images.

SMILE soft X-ray Imager flight model CCD370 pre-flight device characterisation

Throughout the SMILE mission the satellite will be bombarded by radiation which gradually damages the focal plane devices and degrades their performance.In order to understand the changes of the CCD370s within the soft X-ray Imager,an initial characterisation of the devices has been carried out to give a baseline performance level.Three CCDs have been characterised,the two flight devices and the flight spa re.This has been carried out at the Open University in a bespo ke cleanroom measure ment facility.The results show that there is a cluster of bright pixels in the flight spa re which increases in size with tempe rature.However at the nominal ope rating tempe rature(-120℃) it is within the procure ment specifications.Overall,the devices meet the specifications when ope rating at -120℃ in 6 × 6 binned frame transfer science mode.The se rial charge transfer inefficiency degrades with temperature in full frame mode.However any charge losses are recovered when binning/frame transfer is implemented.

Value of MR contrast media in image-guided body interventions

In the past few years,there have been multiple advances in magnetic resonance (MR) instrumentation,in vivo devices,real-time imaging sequences and interventional procedures with new therapies.More recently,interventionists have started to use minimally invasive image-guided procedures and local therapies,which reduce the pain from conventional surgery and increase drug effectiveness,respectively.Local therapy also reduces the systemic dose and eliminates the toxic side effects of some drugs to other organs.The success of MR-guided procedures depends on visualization of the targets in 3D and precise deployment of ablation catheters,local therapies and devices.MR contrast media provide a wealth of tissue contrast and allows 3D and 4D image acquisitions.After the development of fast imaging sequences,the clinical applications of MR contrast media have been substantially expanded to include pre-during-and post-interventions.Prior to intervention,MR contrast media have the potential to localize and delineate pathologic tissues of vital organs,such as the brain,heart,breast,kidney,prostate,liver and uterus.They also offer other options such as labeling therapeutic agents or cells.During intervention,these agents have the capability to map blood vessels and enhance the contrast between the endovascular guidewire/catheters/devices,blood and tissues as well as direct therapies to the target.Furthermore,labeling therapeutic agents or cells aids in visualizing their delivery sites and tracking their tissue distribution.After intervention,MR contrast media have been used for assessing the efficacy of ablation and therapies.It should be noted that most image-guided procedures are under preclinical research and development.It can be concluded that MR contrast media have great value in preclinical and some clinical interventional procedures.Future applications of MR contrast media in image-guided procedures depend on their safety,tolerability,tissue specificity and effectiveness in demonstrating success of the interventions and therapies.

Gold Nanostars-AIE Theranostic Nanodots with Enhanced Fluorescence and Photosensitization Towards Effective Image-Guided Photodynamic Therapy

Dual-functional aggregation-induced photosensitizers(AIE-PSs)with singlet oxygen generation(SOG)ability and bright fluorescence in aggregated state have received much attention in image-guided photodynamic therapy(PDT).However,designing an AIE-PS with both high SOG and intense fluorescence via molecular design is still challenging.In this work,we report a new nanohybrid consisting of gold nanostar(AuNS)and AIE-PS dots with enhanced fluorescence and photosensitization for theranostic applications.The spectral overlap between the extinction of AuNS and fluorescence emission of AIE-PS dots(665 nm)is carefully selected using five different AuNSs with distinct localized surface plasmon(LSPR)peaks.Results show that all the AuNS s can enhance the 1 O2 production of AIE-PS dots,among which the AuNS with LSPR peak at 585 nm exhibited the highest 1 O2 enhancement factor of15-fold with increased fluorescence brightness.To the best of our knowledge,this is the highest enhancement factor reported for the metalenhanced singlet oxygen generation systems.The Au585@AIE-PS nanodots were applied for simultaneous fluorescence imaging and photodynamic ablation of HeLa cancer cells with strongly enhanced PDT efficiency in vitro.This study provides a better understanding of the metal-enhanced AIE-PS nanohybrid systems,opening up new avenue towards advanced image-guided PDT with greatly improved efficacy.

Evaluation of axis alignment and refractive results of toric phakic IOL using image-guided system

AIM: To evaluate accuracy of axis alignment and refractive results of toric phakic intraocular lens(IOL) implantation using a digital imaging system. METHODS: This retrospective study investigated toric implantable collamer lens(ICL) implantation in 30 eyes of 21 patients with myopic astigmatism more than 2.0 D guided with digital imaging system. Data were collected during the first week after phakic IOL implantation.RESULTS: Thirty eyes of 21 patients were included in our study. Patients includes 9 males and 12 females. The mean age of the patients was 26.5±7.1(range 21-44)y. The mean preoperative manifest astigmatism was 3.2±1.7(range from 2.25 to 4.75) D. The mean postoperative uncorrected distance visual acuity(UCDVA) were 0.07±0.07(range from 0.1 to 0.0) log MAR. The mean postoperative residual refractive cylinder was 0.25±0.29(range 0-0.75) D. Eyes with postoperative residual refractive cylinder of 0.5 D or less represented 80%(24 eyes). The mean postoperative toric IOL misalignment measured by the OPD scan III was 1.9°±1.45°(range from 0 to 5°). CONCLUSION: Image guided system allows accurate alignment of toric ICL. This is associated with good postoperative visual acuity and low residual refractive astigmatism which correlates with the precision of toric phakic IOL alignment.

MRF-Based Multispectral Image Fusion Using an Adaptive Approach Based on Edge-Guided Interpolation

In interpretation of remote sensing images, it is possible that some images which are supplied by different sensors become incomprehensible. For better visual perception of these images, it is essential to operate series of pre-processing and elementary corrections and then operate a series of main processing steps for more precise analysis on the images. There are several approaches for processing which are depended on the type of remote sensing images. The discussed approach in this article, i.e. image fusion, is the use of natural colors of an optical image for adding color to a grayscale satellite image which gives us the ability for better observation of the HR image of OLI sensor of Landsat-8. This process with emphasis on details of fusion technique has previously been performed;however, we are going to apply the concept of the interpolation process. In fact, we see many important software tools such as ENVI and ERDAS as the most famous remote sensing image processing tools have only classical interpolation techniques (such as bi-linear (BL) and bi-cubic/cubic convolution (CC)). Therefore, ENVI- and ERDAS-based researches in image fusion area and even other fusion researches often don’t use new and better interpolators and are mainly concentrated on the fusion algorithm’s details for achieving a better quality, so we only focus on the interpolation impact on fusion quality in Landsat-8 multispectral images. The important feature of this approach is to use a statistical, adaptive, and edge-guided interpolation method for improving the color quality in the images in practice. Numerical simulations show selecting the suitable interpolation techniques in MRF-based images creates better quality than the classical interpolators.