Visible Color Image Research Articles

Inkjet printing of TiO2/AlOOH heterostructures for the formation of interference color images with high optical visibility.

This paper describes a practical approach for the fabrication of highly visible interference color images using sol-gel ink technique and a common desktop inkjet printer. We show the potential of titania-boehmite inks for the production of optical heterostructures on various surfaces, which after drying on air produce optical solid layers with low and high refractive index. The optical properties of the surface heterostructures were adjusted following the principles of antireflection coating resulting in the enhancement of the interference color optical visibility of the prints by as much as 32%. Finally, the presented technique was optimized following the insights into the mechanisms of the drop-surface interactions and the drop-on-surface coalescence to make it suitable for the production of even thickness coatings suitable for printing at a large scale. We propose that the technology described herein is a promising new green and sustainable approach for color printing.

Hybrid fusion and interpolation algorithm with near-infrared image

Silicon-based digital cameras can record visible and near-infrared (NIR) information, in which the full color visible image (RGB) must be restored from color filter array (CFA) interpolation. In this paper, we propose a unified framework for CFA interpolation and visible/NIR image combination. To obtain a high quality color image, the traditional color interpolation from raw CFA data is improved at each pixel, which is constrained by the corresponding monochromatic NIR image in gradient difference. The experiments indicate the effectiveness of this hybrid scheme to acquire joint color and NIR information in real-time, and show that this hybrid process can generate a better color image when compared to treating interpolation and fusion separately.

基于区域检测与非下采样轮廓波变换的红外与彩色可见光图像融合

An infrared and color visible image fusion method based on Snake model region detection and non-subsampled contourlet transform(NSCT) is presented. In this method, first of all, the luminance component is extracted by using IHS(intensity, hue, saturation) color space conversion for color visible images and the target region of infrared images is detected by adopting Snake model. Then NSCT decomposition is utilized for the luminance component and target replaced infrared image. Image fusion is done by using the largest pixels absolute value sum for the high frequency coefficient and the weighted fusion rules based on brightness mapping technology for the low frequency coefficient. NSCT inverse transform is adopted to obtain the brightness of the image fusion for the fusion coefficients. Finally, the color space inverse transformation is used to acquire fusion images. Experimental results show that the proposed fusion method can not only maintain a high resolution and natural colors of the visible image, but also accurately retain the target information detected in the infrared image. Compared with other methods, fusion images with a better visual effect and comprehensive indicator can be achieved.

Design and Implementation of Invisible and Visible Color Image Watermarkingwith Netbeans IDE

of this paper is to present design and implementation of invisible and visible color image watermarking technique. The algorithms of individual category with implementations in Java Netbeans and test outcomes are presented to focus requirements in visible and invisible techniques. Though Matlab, Scilab, Octave are used for image processing, Net beans IDE is top of line Integrated Development Environment for Java development preferred for platform independent project development in industry and research work. The paper illustrates handling of visible text watermarking, visible logo watermarking and invisible watermarking with Java Netbeans implementation. The main objective of the paper is to focus on design and implementation with help of algorithms with test results presented here, instead of proving quality metrics of individual algorithm implemented in this paper. .

Historical document image restoration using multispectral imaging system

Thousands of valuable historical documents stored on the shelves of national libraries throughout the world are waiting to be scanned in order to facilitate access to the information they contain. The first major problem faced is degradation, which renders the visual quality of the document very poor, and in most cases, difficult to decipher. This work is part of our collaboration with the BAnQ (Bibliothèque et Archive Nationales de Québec), which aims to propose a new approach to provide the end user (historian, scholars, researchers, etc.) with an acceptable visualization of these images. To that end, we have adopted a multispectral imaging system capable of producing images in invisible lighting, such as infrared lights. In fact, in addition to visible (color) images, the additional information provided by the infrared spectrum as well as the physical properties of the ink (used on these historical documents) will be further incorporated into a mathematical model, transforming the degraded image into its new clean version suitable for visualization. Depending on the degree of degradation, the problem of cleaning them could be resolved by image enhancement and restoration, whereby the degradation could be isolated in the Infrared spectrum, and then eliminated in the visible spectrum. The final color image is then reconstructed from the enhanced visible spectra (red, green and blue). The first experimental results are promising and our aim in collaboration with the BAnQ, is to give this documentary heritage to the public and build an intelligent engine for accessing the documents.

基于彩色传递和信息熵的红外与彩色可见光图像融合

基于彩色传递和信息熵的红外与彩色可见光图像融合

Visible and infrared image registration using trajectories and composite foreground images

The registration of images from multiple types of sensors (particularly infrared sensors and visible color sensors) is a step toward achieving multi-sensor fusion. This paper proposes a registration method using a novel error function. Registration of infrared and visible color images is performed by using the trajectories of moving objects obtained using background subtraction and simple tracking. The trajectory points are matched using a RANSAC-based algorithm and a novel registration criterion, which is based on the overlap of foreground pixels in composite foreground images. This criterion allows performing registration when there are few trajectories and gives more stable results. Our method was tested and its performance quantified using nine scenarios. It outperforms a related method only based on trajectory points in cases where there are few moving objects.

Integrating Motion and Segmentation for Road Scene Labeling

Structure from motion (SfM) and appearance-based segmentation have played an important role in the interpretation of road scenes. The integration of these approaches can lead to good performance during interpretation since the relation between 3D spatial structure and 2D semantic segmentation can be taken into account. This paper presents a new integration framework using an SfM module and a bag of textons method for road scene labeling. By using a multiband image, which consists of a near-infrared and a visible color image, we can generate better discriminative textons than those generated by using only a color image. Our SfM module can accurately estimate the ego motion of the vehicle and reconstruct a 3D structure of the road scene. The bag of textons is computed over local rectangular regions: its size depends on the distance of the textons. Therefore, the 3D bag of textons method can help to effectively recognize the objects of a road scene because it considers the object's 3D structure. For solving the labeling problem, we employ a pairwise conditional random field (CRF) model. The unary potential of the CRF model is affected by SfM results, and the pairwise potential is optimized by the multiband image intensity. Experimental results show that the proposed method can effectively classify the objects in a 2D road scene with 3D structures. The proposed system can revolutionize 3D scene understanding systems used for vehicle environment perception.

A Rapid Fusion Algorithm of Infrared and the Visible Images Based on Directionlet Transform

Direction transform; image fusion; infrared images; fusion rule; anisotropic Abstract Based on analysing the feature of infrared and the visible, this paper proposed an improved algorithm using Directionlet transform.The feature is like this: firstly, separate the color visible images to get the component images, and then make anisotropic decomposition for component images and inrared images, after analysing these images, process them according to regional energy rules ,finally incorporate the intense color to get the fused image. The simulation results shows that,this algorithm can effectively fuse infrared and the visible image, moreover, not only the fused images can maintain the environment details, but also underline the edge features, which applies to fusion with strong edges, therefore,this algorithm is of robust and convenient.

Multispectral infrared image classification using filters derived from independent component analysis

Spectral-spatial independent component analysis (ICA) basis functions of visible color images are similar to some processing elements in the human visual systems in that they resemble Gabor filters and show color opponencies. In this research we studied combined spectral-spatial ICA basis functions of multispectral mid wave infrared (MWIR) images. These ICA spectral-spatial basis functions were then used as filters to extract features from multispectral MWIR images for classification. The images were captured in the 3.0–5.0 µm, 3.7–4.2 µm, and 4.0–4.5 µm bands using a multispectral MWIR camera. In the proposed algorithm, phase relationships between the basis functions indicate how the extracted features from the different spectral band images can be combined. We used classification performance to compare features obtained by filtering using multispectral ICA basis functions, multispectral principal component analysis basis functions, and Gabor filters.

A Bayesian Super-Resolution Approach to Demosaicing of Blurred Images

Most of the available digital color cameras use a single image sensor with a color filter array (CFA) in acquiring an image. In order to produce a visible color image, a demosaicing process must be applied, which produces undesirable artifacts. An additional problem appears when the observed color image is also blurred. This paper addresses the problem of deconvolving color images observed with a single coupled charged device (CCD) from the super-resolution point of view. Utilizing the Bayesian paradigm, an estimate of the reconstructed image and the model parameters is generated. The proposed method is tested on real images.

Development of a simulator for radiographic image optimization

A software package, incorporating two computational patient phantoms, has been developed for optimizing X-ray radiographic imaging. A tomographic phantom, visible photographic Man tomographic phantom (VIP-Man), constructed from Visible Human anatomical color images is used to simulate the scattered portion of an X-ray system using the Electron Gamma Shower National Research Council (EGSnrc) Monte Carlo code. The primary portion of an X-ray image is simulated using the projection ray-tracing method through the Visible Human CT data set. To produce a realistic image, the software simulates quantum noise, blurring effects, lesions, detector absorption efficiency, and other imaging artifacts. The primary and scattered portions of an X-ray chest image are combined to form a final image for future observer studies and image quality analysis. Absorbed doses in organs and tissues of the segmented VIP-Man phantom were also obtained from the Monte Carlo simulations. This paper presents methods of the simulator and preliminary results.