最新刊期
卷 19 ， 期 7 ， 2014
- 摘要：Until recently, printing technology has been a kind of mainstream technology for color image reproduction. Printer characterization aims at establishing the relationship between the input control values of the printer and its output colors. It is the core of color accuracy controlling for each image pixel during the printing process. Spectral-based printer characterization conquers the metamerism problem of colorimetric characterization and thus can achieve unconditional matched color reproduction, which represents the highest level of color reproduction in the state of the art. Based on the extensive and in-depth investigation of existing articles, in this paper we review the research development of the main topics of spectral-based printer characterization and present a comprehensive survey of various existing methods, with more than 60 related reviewed pieces of literature. This review employs the famous Yule-Nielsen modified spectral Neugebauer model as an example; critically reviews the research of spectral-based printer characterization from the aspects of ink limitation algorithm development, spectral prediction model establishment, spectral separation method development, and image color match evaluation metric optimization; and discusses future research trends according to the existing problems of the current study. Based on the comprehensive survey of the current research situation, significant progress has been made in the field of ink limitation algorithm development, spectral prediction modeling, and spectral separation algorithm development. However, in spite of more than 20 years of research and development in this field, the general problem of how to precisely and efficiently conduct spectral-based printer characterization still exists, not only because of the high dimensionality of spectral data but also because of the variety of actual applications. Therefore, in many aspects, such as improving modeling efficiency, enhancing model applicability, interpreting the model's physical meaning, and optimizing evaluation metrics, further work is still needed. Spectral-based printer characterization is an essential means for high-fidelity color reproduction and will continue to play an important role in the image reproduction workflow. However, because of its interdisciplinarity among several subjects, which involve spectroscopy and colorimetry theory, halftone color rendering theory, optimization theory, human vision theory, and digital halftoning technology, difficulties surely exist. This paper introduces the main topics and analyzes the current research situation of spectral-based printer characterization. This overview aims to help researchers in this area to have a more intuitive understanding of existing spectral-based printer characterization methods and to attract more researchers' attention in this field. Given the space limitation, some issues are not discussed in detail.关键词：spectral reflectance;printer characterization;ink limitation;color prediction;color separation;spectral match metric3324|235|0更新时间：2024-05-07
- 摘要：A good visual effect has been the main target of present researchers in image reconstruction,and accurate local area reconstruction has been neglected. However,with the development of image analysis and recognition,more and more reconstructed images have been used for feature extraction. Therefore,accurate image reconstruction is arousing researchers' attention. At the same time,to achieve a higher reconstruction efficiency is also being taken seriously because of the real-time requirement and video processing. Pointing to the two problems above,a new algorithm is proposed in this paper. The stable field model is used to describe the image local region in this paper,a reconstructing model based on point-source influence function is proposed, and the directional derivative is used to analyze the calculation methods of the influence function. Given that it is the stable result of the interaction between the surface texture and structure of the object and light,a stationary image can be regarded as a stable energy field,so that we propose a stable field model of the image local region. In this model the missing pixel is the "point" and the known pixel is the "source". Then,a stable field equation of the image local region is set up according to the model. After the equation is solved,a new reconstruction model of the image local region based on the point-source influence function is proposed,which aims at reconstructing each missing pixel accurately by calculating the influence of the known pixels around. Finally,according to the directional derivative of the stable field,a method to calculate the point-source influence function is determined by analyzing both the similarities and differences between the missing pixel and the known,so that the reconstruction model could be achieved. In the reconstruction model,the missing pixels are assigned values one by one;before this,the influence function of each "source" around the "point" would be calculated first. Because both the calculation and the assignment to each missing pixel are as accurate as possible,compared with traditional reconstruction algorithms,the proposed algorithm achieves a better effect in accurate reconstruction. The proposed algorithm reconstructs damaged edges and texture more clearly than traditional ones and at the same time keeps a good visual effect. Moreover,because there are no iterative computations in the reconstruction process,the proposed algorithm has higher efficiency than traditional ones,which experimental results confirm that. Based on the foundation of the image local region's stable field model,a new reconstruction model for the image local region is proposed,and it is achieved by calculating the point-source influence function with an algorithm based on the field directional derivative. Different from traditional ones,the proposed algorithm shifts the attention from the total visual effect to the reconstruction of each missing pixel,so that it achieves a more accurate reconstruction for damaged images. In addition, the lack of iterative computations makes it more efficient than traditional ones.关键词：stable field;point-source influence function;field directional derivative;reconstructing image local region2931|313|0更新时间：2024-05-07
- 摘要：The light field camera has aroused more attention for its ability to refocus after the fact. However, researches of light field camera are often restricted by the acquisition of raw image and calibration parameters. Based on the Lytro camera,which is the only off-the-shelf light field camera for ordinary consumers,this paper develops systematical methods for acquisition of light field images, correction， and refocusing. By analyzing the operating principle,algorithms and file structure of the Lytro camera,we present a set of complete schemes that accomplish the data extraction from raw light field,decoding,color correction,calibration and correction for microlens array. Furthermore,based on fractional Fourier transform,a refocus method for light field images is proposed. Experiments demonstrate that our systematical scheme is feasible and correct,and the refocus method has satisfactory performance. This paper presents the methods for acquisition and calibration of light field images and then implements the refocusing in frequency domain by using the fractional Fourier transform. Experimental results from two Lytro cameras verify that our proposed method can correctly obtain the image data and camera parameters,and the refocusing algorithm exhibits better performance.关键词：light field camera;Lytro camera;refocus;fractional Fourier transform5290|285|0更新时间：2024-05-07
- 摘要：Image morphing algorithm is a branch of image-based rendering(IBR). Normally, it extracts features and matches features by human-computer interaction. However,there are problems in such human-computer interaction algorithms.When occlusion areas are processed, ghosting and blurring have a great chance to occur which are fatal to image morphing algorithms. All these phenomena lead to poor experimental results in the same scene. The implementations of old-fashioned image morphing algorithms are always complicated and inefficient and usually not suitable for practical application. In order to solve these problems,we propose a novel and efficient image morphing algorithm based on multi-feature fusion in this paper. In spite of marking two relevant images on edges,corners, and rich-texture areas by human-computer interaction,our proposal innovatively extracts multiple-image feature information (such as Surf feature,Harris feature, and Canny feature) with multi-feature fusion matching, which obtains a properly distributed triangle mesh pair with correct correspondence. Then, automatic image interpolation is achieved by the conjunction of triangle mesh and image morphing. We select Surf feature,Harris feature, and Canny feature as basic features. First,we extract these image features from the original image and destination image. Then, we process Surf feature based on Delaunay triangulation to obtain an initial triangle mesh. It is fusion matched with Harris features or other image features. According to this step,an accurate and uniform triangle mesh is acquired. We also define a matching cost function,a feature point of color intensity cost, and a grade matching cost to optimize the matching of features. It improves the accuracy of image feature matching. Finally,the image is transformed based on the acquired triangle mesh to a virtual view image between the original image and destination image. In the conventional image morphing algorithm,the system will take a long time to choose feature points manually which is not suitable for practical application. In our proposal,the step of extracting image features and matching image features is achieved automatically so that it compensates the inefficiency of traditional image morphing algorithms. Compared with the method of human-computer interaction,the performance of our proposal is extremely better in details such as edges,corners, and rich-texture areas. Theoretic analysis and experimental results indicate that automatically extracted and matched image feature method effectively reduces the manual operation,and multi-feature fusion effectively restricts the ghosting produced at edges and occlusion areas in image morphing. Image morphing algorithm is widely used in domains such as special effects in movis and 3D TV. However, the complicated and excessive implementation of traditional image morphing algorithms restricts the range of application. In this paper,a new approach of fusion matching is proposed. During this approach,different types of image features are effectively matched to improve image morphing algorithm. Through the questionnaire survey to the experimental results,91% of the participants think that the algorithm effectively improves the image morphing result. With the proposed approach,image morphing algorithm has great potential in the application of other domains.关键词：multi-feature;fusion matching;automatic;image morphing3972|338|0更新时间：2024-05-07
- 摘要：The enhancement of fingerprint plays an important role in automatic fingerprint identification system. It is the foundation that extracts fingerprint minutiae reliably. In order to make up for the defects of fingerprint image and enhance low quality fingerprint image effectively,this paper proposes a novel algorithm by using spectrum diffusion to enhancing the fingerprint image. The basic idea of the algorithm is to enhance the fingerprint by using block quality assessment and block spectrum matched filter in the frequency domain. First,the quality assessment result of block image is obtained according to the point direction coherence parameter. Second,this paper studies the diffusion characteristics of composite window spectrum,and then design out a block spectrum matched filter based on linear fuzzy k-means clustering and 2D Butterworth band-pass filter of one order adaptive bandwidth and two-dimensional Gaussian window. At last,the composite window spectrum is enhanced by block spectrum matched filter according to the block quality grade. Experiments on the database of FVC 2004 show that,compared with the previously proposed enhancement methods,the proposed method is more accurate and more robust against noise,and has a prominent effect on both low quality and high quality fingerprint image. This paper presents a fingerprint enhancement using filter method of weak parameters dependencies in frequency domain. This method is of good fault tolerant. The experimental results show that both high quality and low quality fingerprint image can be enhanced effectively.关键词：fingerprint identification;block quality assessment;block spectrum matched filter;spectrum diffusion3409|291|0更新时间：2024-05-07
- 摘要：The application of central projection transform combines region-based methods with contour-based methods, and it is an effective invariant feature extraction algorithm. However,current literature lacks of further discussion of robustness to noise,and only a few simple theoretical and experimental results can be found. In this paper,we mainly study the robustness to noise of central projection transformation. Using the ideas of analysis for the robustness to noise of Radon transformation, we discuss the robustness to noise of central projection transformation. Theoretical results show that central projection transform is very robust to white noise and salt and pepper noise,and its robustness is affected by the size of the input noise image,the percentage of the shape region,and the level of noise. Theoretical analytic and experiment results show that central projection transform is very robust to white noise and salt and pepper noise,and its robustness is affected to on the size of the input noise image,the percentage of the shape region,and the level of noise.关键词：central projection transformation;Gaussian noise;salt and pepper noise;robustness to noise3139|237|0更新时间：2024-05-07
- 摘要：A multi-channel Haar-like feature based object tracking algorithm with multiple instance learning(MIL)is proposed in this paper. It overcomes the disadvantages of the MIL algorithm such as using limited information and not replacing weak features for color videos. First,in the original MIL algorithm, the color video frame is tracked with a single channel's information or by simply converting it to grayscale images. This may lose some feature information. Therefore,we propose that the target is represented with Haar-like features generated from three channels of RGB with completely random location,size and channel to represent the target better. Next,Haar-like features could not be replaced in the original MIL algorithm,which has difficulty reflecting the changes of the target and the background. Thus, we replace some weakest discriminative Haar-like features with new randomly generated Haar-like features when weak classifiers are selected. It introduces new information to the target model and adapts to the dynamic changes of the target appearance. The experiment on eight challenging color videos shows that the proposed method obtains optimal performance compared with the original multiple instance learning algorithm,weighted multiple instance learning algorithm, and distribution field based algorithm. It not only obtains the minimal average center location errors,but also obtains a higher average accuracy rate by 52.85%,34.75% and 5.71% than the other three algorithms. The proposed algorithm obviously promotes the tracking results compared with the original MIL algorithm on color videos by generating Haar-like features from three RGB channels and replacing some weakest discriminative Haar-like features in real time. It extends the application prospect of the MIL algorithm.关键词：object tracking;multiple instance learning;multi-channel Haar-like feature;weak classifier replacement3773|353|0更新时间：2024-05-07
- 摘要：In process of outdoor autonomous mobile robot visual navigation, shadows, causing cracks and irregular road boundary are encountered, which make the detection algorithms not so robust. The objectives of this paper are to resolve these problems. The proposed method in this paper is called a fast adaptive road detection method evolving adjustable gray thresholds per frame. First, a two-dimensional discrete wavelet analysis is used for road image decomposition and reconstruction. After comparing the approximate wavelet reconstruction of the road image in multiple-levels, a best resolution grade is determined which does not affect the "road-non-road" classification. In the best scale space, the grayscale maximum variance between-class and minimum variance within-class are used to create a fitness function, and the improved genetic algorithm is used in road image segmentation with each frame having an adaptive grayscale segmentation threshold. After that, the accurate road boundary is found, and if using the nearest two boundaries to calculate the central position of the road, the robot can know its driving directions. Content of main experiments: In this paper, a small autonomous land vehicle is used as a research platform, and the algorithm is tested by the outdoor path driving video of a mobile robot provided by CMU. The experimental results show that this method can detect the boundaries robustly under varying road conditions including shadows, cracks, and illumination changes. The real-time performance of the road detection system is good. The robot with this algorithm can run at a speed of 30 km/h on the school road covered with shadows, and the process rate of the vision system can reach to 20 ms per frame. Comparisons with reviewed researches: This segmentation method showed stronger self-adaptability to the environment than the traditional gray level histogram based segmentation method. A robust detection for the outdoor road is realized by the method of this paper. The proposed method in this paper can be seen as a robust method to the outdoor autonomous mobile robot's unstructured road detection, and should been extended.关键词：autonomous mobile robot;wavelet compression;genetic algorithms;adaptive road detection3923|307|0更新时间：2024-05-07
- 摘要：Sparse coding using learned dictionaries can adaptively represent signals. However, the similarity among the signals that are encoded in traditional dictionary are lost due to a lack of correlations between atoms. Considering the robustness and discriminative power of structured sparse representation, the building of the structured dictionary becomes an important task. We conceive a framework of tree-structured dictionary by introducing a constraint for the data point code path (programming the index from the upper layer to the next layer) according to the standard convex optimization dictionary-learning algorithm. Experimental results on the KTH human action database show that local descriptor codes with learned tree-structured dictionary have good robustness and discriminative and demonstrate that our algorithm generally obtains higher recognition accuracy than other similar methods. We achieve an accuracy rate of 97.99% using histograms of oriented 3D spatial-temporal gradients(HOG3D). From our experiments, we observe that the encoding of signals using the constructed dictionary has good robustness and discrimination, and is preferable for the task of classification.关键词：action recognition;sparse coding;local descriptor;tree-structured dictionary3136|249|0更新时间：2024-05-07
- 摘要：Caustic rendering plays an important part in the research of photorealistic image rendering. Based on programmable GPUs, image-based photon mapping renders fast but suffers from artifacts caused by sampling and computing approximately. To overcome this drawback, this paper proposes a fast method called virtual object-based photon beam tracing (VOBPBT) to render caustic effects. VOBPBT originally defines the photon-path map and then constructs the map. It also presents a way to find caustic triangles in the photon-path map and splat them onto the caustic map. This method can recursively render reflective and refractive effects as well as high-frequency caustic effects realistically in an interactive speed. VOBPBT is useful in interactive computer-aided simulation, computer games, as well as virtual tours.关键词：caustic;beam tracing;photon mapping;virtual objects;GPU3034|232|0更新时间：2024-05-07
- 摘要：To protect the copyright of 3D model data, a scheme of visible watermark for 3D mesh models that is perceptible in the 3D view and the wireframe view is proposed. A new visible watermarking algorithm for 3D triangle meshes is established as well. First, the region to embed is projected onto the 2D plane. Then, the watermark in vector format is embedded into the region. Finally, the region is projected onto the original meshes. The core process of this approach is to separate the triangles into two parts. One part is in the watermark, and the other part is outside the watermark. The Sutherland-Hodgeman algorithm for clipping polygons is altered and used in the embedding. To verify the effectiveness of the proposed algorithm, experiments are conducted with 3D model data. The algorithm keeps the visual characteristics of the original model well, and the watermark is plainly visible in both views. The increment of the size of the embedded data is about 10 percent. The proposed approach is an effective way to embed watermark into triangle meshes and can be used in the copyright protection of 3D mesh models.关键词：mesh model;visible watermark;3D view;wireframe view;polygon clipping2749|272|0更新时间：2024-05-07
- 摘要：The complexity of the geometry and topological structure of 3D trees not only makes the construction of realistic 3D tree models very complex but also increases data for the points and the faces saved in these model files. As to the complexity of constructing 3D trees and the large volumes of model data, we propose a construction method of lightweight 3D tree models supporting skeleton personalized editing in this paper. Based on extracting skeleton structures of existing trees models, this method can personalize 3D tree models through the interaction to generate a new frame structure, and adopts branches and crown simplification to realize the lightweight construction of trees models. The method can quickly create lightweight tree models that will reduce the visualization rendering time of 3D tree models as well as personalized edits to design the topological structure of the trees by using skeletons that increase the external form diversity of the same tree varieties. The applications show that the construction method of lightweight 3D tree models can not only build 3D tree models with different external forms, but also enable simplified 3D tree models to be visualized in wireless networks, mobile terminals, and other resource-limited circumstances.关键词：three-dimensional tree;tree skeleton;personalization editing;lightweight;texture template2701|228|0更新时间：2024-05-07
- 摘要：Polar format algorithm is an imaging approach for spotlight mode synthetic aperture radar (SAR). It increases the load of data transmission and storage severely because of the greater synthetic aperture length. Synthetic aperture radar imaging by compressive sensing can reduce the sampling rate. Previous studies result in a decrease in image quality because they assume that the two dimensions of images are separable and ignore the range migration. An imaging approach based on range-cross compressive sensing is presented. It can correct the range migration and ensure the range and range-cross resolution of the image. The method introduces the Fourier basis varying with the range spatial frequency, reconstructing the image based on compressive sensing. It ensures the range and range-cross resolution because it may be an efficient substitute for Polar format algorithm range-cross interpolation and eliminates the range migration. The simulations and live data processing results show the validity of the proposed approach.关键词：potar fonmat algorilhm (PFA);compressive sensing;range interpolation;range-cross interpolation;range migration correction2917|239|0更新时间：2024-05-07
- 摘要：Target contours provide valuable shape information that can be used in pose estimation and target recognition. Therefore, target contour extraction in synthetic aperture radar (SAR) image has drawn much attention around the world. Given the multiplicative noise inherent in SAR image, traditional target contour extraction methods fail to process SAR images. To solve this problem, this paper proposes a new active contour model that combines the attributes of both edges and regions. Based on real SAR images, this paper analyzes the vector field convolution active contour model and the region competition active contour model. The two active contour models have their own advantages and complement each other. Therefore, we combine the two active contour models to obtain a new active contour model that can be used for target contour extraction in SAR image. The experiments are conducted based on real SAR images, and results show that the proposed method can deal with the characteristics of SAR image, such as low signal-to-noise ratio and blurred target edges. It can accurately locate the contours of the targets in SAR image. The proposed method can be applied to SAR image interpretation to extract target contours to provide excellent input information for subsequent tasks in SAR image interpretation, such as automatic identification and feature-level image fusion.关键词：synthetic aperture radar;target contour extraction;active contour model;likelihood ratio;vector field convolution;G0 distribution3297|313|0更新时间：2024-05-07
- 摘要：The eye tracking technique is one of the most advanced state-of-the-art physiological measurements to non-intrusively get human vision attention. Eye tracking technology is introduced and its application to the research of image quality perception is discussed. The first image quality assessment (IQA) database with eye tracking data, called XJTU_ETSS, is established for IQA research. Finally, heat map visualization is utilized on the XJTU_ETSS database to show the visual attention distribution differences within and between the original and distorted image groups. Single stimuli subject image assessment method is chosen on Tobii TX300 eye tracker with 60 Hz sampling rate to setup the database including 900 original and distorted images and 49 subjects. To visualize the eye tracking-based visual attention, methods as gaze plot and heat map are introduced in the paper. The distribution of values around a raw gaze data is accomplished by using an approximation to the Gaussian curve-a cubic hermite spline polynomial (cspline). According to the data of XJTU_ETSS, the count-based heat map, which shows the generality of the distribution of the visual attention of different subjects, is utilized to quantitatively and qualitatively analyze the different distributions of visual attention on original and distorted images. First, the total number of interest areas on original images is larger and more concentrated than that on distorted images. Second, heat maps of the distorted images, such as awgn, gb and hfn have no obvious areas of interest (AOIs). Instead, the attention of the observers is spread all over the images because those kinds of distortions added useless information to destroy the original image. Third, heat maps of the distorted images, such as jp2k, jpeg and quan don't have as many AOIs as the original images. Because those kinds of distortions subtract information to compress the image, so that the detail of the original images are lost and there are no AOIs on the detail parts of such kinds of distorted images. According to the initial analysis on XJTU_ETSS, eye tracking techniques can intuitively reveal the features of human visual attention during original and distorted image reading. Such advantages can greatly contribute to the better visual attention-based subject image quality assessment algorithm in future and more comprehensive and thorough understanding of physiological and psychological mechanisms of human vision system.关键词：eye tracking techniques;image quality perception;eye tracker;image quality assessment database;heat map5142|261|0更新时间：2024-05-07
- 摘要：With the development of Web 2.0, social websites centered on user-generated content are arising. Therefore, tag-based image retrieval becomes more and more important. However, the image tags that users upload are incomplete because users label images freely and arbitrarily and thus decrease the performance of image retrieval. To solve the problem of image tag incompletion, this paper proposes an algorithm based on regularized non-negative matrix factorization to enrich the tags of social images and make these tags complete. This proposed algorithm casts the original tag-image matrix to a latent low-rank space and discovers the correlations between tags with the matrix factorization technique. The relationships among tags are utilized to enrich tags for social images. Meanwhile, the overall visual diversity as a regularization term is utilized to restrict the impact of content-irrelevant tags and enrich image tags. This paper constructs comparison experiments on images downloaded from sharing website Flickr. Accuracy is used to evaluate these comparison experiments. These experiments demonstrate the effectiveness of our proposed algorithm for enriching image tags. Compared with state-of-the-art approaches, our approach could improve average accuracy by 12.3%. This paper proposes a regularized non-negative matrix factorization framework with overall visual diversity as the regularization term and enriches the tags of images effectively. Our proposed algorithm can solve the problem of incomplete tags.关键词：image tag enrichment;regularization;non-negative matrix factorization;projected gradient method4383|256|0更新时间：2024-05-07
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