Fusion on Citrus Image Data from Cold Mirror Acquisition System

2012 ◽  
Vol 2 (4) ◽  
pp. 11-24 ◽  
Author(s):  
Peilin Li ◽  
Sang-Heon Lee ◽  
Hung-Yao Hsu
Keyword(s):  
Near Infrared ◽  
Color Image ◽  
Infrared Image ◽  
Image Data ◽  
Acquisition System ◽  
Support Vector ◽  
Self Organizing Map ◽  
Visible Image ◽  
Low Pass ◽  
Low Dimensional

In this paper, an image fusion is presented to improve the citrus identification by filtering the incoming data from two cameras. The citrus image data has been photographed by using a portable bi-camera cold mirror acquisition system. The prototype of the customized fixture has been manufactured to position and align a classical cold mirror with two CCD cameras in relative kinematic position. The algorithmic registration on the pairwise images has been bypassed by both the spatial alignment of two cameras with recourse of software calibration and the triggering synchronization in temporal during the photographing. The pairwise frames have been fused by using the Daubechies wavelets decomposition filters. The pixel level fusion index rule is proposed to combine the low pass coefficients of the visible image and the low pass coefficients of the near-infrared image convoluted by the complementary of entropy filter from the visible low pass coefficients. In the study, the fused artifact color image and the non-fused color image have been processed and compared by some classification methods such as low dimensional projection, self-organizing map and the support vector machine.

scholarly journals Visible and Near-Infrared Image Synthesis Using PCA Fusion of Multiscale Layers

2020 ◽  
Vol 10 (23) ◽  
pp. 8702
Author(s):  
Dong-Min Son ◽  
Hyuk-Ju Kwon ◽  
Sung-Hak Lee
Keyword(s):  
Near Infrared ◽  
Infrared Image ◽  
Principal Component ◽  
Image Synthesis ◽  
Local Contrast ◽  
Laplacian Pyramid ◽  
Visible Image ◽  
Color Compensation ◽  
Mixing Method ◽  
Pca Algorithm

This study proposes a method of blending visible and near-infrared (NIR) images to enhance their edge details and local contrast based on the Laplacian pyramid and principal component analysis (PCA). In the proposed method, both the Laplacian pyramid and PCA are implemented to generate a radiance map. Using the PCA algorithm, the soft-mixing method and the mask-skipping filter were applied when the images were fused. The color compensation method uses the ratio between the radiance map fused by the Laplacian pyramid and the PCA algorithm and the luminance channel of the visible image to preserve the chrominance of the visible image. The results show that the proposed method improves edge details and local contrast effectively.

scholarly journals Analysis of glacier facies using satellite techniques

1991 ◽  
Vol 37 (125) ◽  
pp. 120-128 ◽  
Author(s):  
Richard S. Williams ◽  
Dorothy K. Hall ◽  
Carl S. Benson
Keyword(s):  
Near Infrared ◽  
Infrared Image ◽  
Image Data ◽  
Landsat Data ◽  
Near Infrared Reflectance ◽  
Outlet Glacier ◽  
Northern Margin ◽  
Ice Cap ◽  
Snow Line ◽  
Wet Snow

AbstractThe different snow and ice types on a glacier may be subdivided according to the glacier-facies concept. The surficial expression of some facies may be detected at the end of the balance year by the use of visible and near-infrared image data from the Landsat multispectral scanner (MSS) and thematic mapper (TM) sensors. Ice and snow can be distinguished by reflectivity differences in individual or ratioed TM bands on Brúarjökull, an outlet glacier on the northern margin of the Vatnajökull ice cap, Iceland. The Landsat scene shows the upper limit of wet snow on 24 August 1986. Landsat-derived reflectance is lowest for exposed ice and increases markedly at the transient snow line. Above the slush zone is a gradual increase in near-infrared reflectance as a result of decreasing grain-size of the snow, which characterizes drier snow. Landsat data are useful in measuring the areal extent of the ice facies, the slush zone within the wet-snow facies, the snow facies (combined wet-snow, percolation and dry-snow facies), and the respective positions of the transient snow line and the slush limit. In addition, fresh snowfall and/or airborne contaminants, such as soot and tcphra, can limit the utility of Landsat data for delineation of the glacier facies in some cases.

Self-Organizing Map Learning Nonlinearly Embedded Manifolds

2005 ◽  
Vol 4 (1) ◽  
pp. 22-31 ◽  
Author(s):  
Timo Similä
Keyword(s):  
Learning Algorithm ◽  
Image Data ◽  
High Dimensional ◽  
Locally Linear Embedding ◽  
Complex Data ◽  
Dimensional Manifold ◽  
Self Organizing Map ◽  
Training Strategy ◽  
Low Dimensional ◽  
Self Organizing

One of the main tasks in exploratory data analysis is to create an appropriate representation for complex data. In this paper, the problem of creating a representation for observations lying on a low-dimensional manifold embedded in high-dimensional coordinates is considered. We propose a modification of the Self-organizing map (SOM) algorithm that is able to learn the manifold structure in the high-dimensional observation coordinates. Any manifold learning algorithm may be incorporated to the proposed training strategy to guide the map onto the manifold surface instead of becoming trapped in local minima. In this paper, the Locally linear embedding algorithm is adopted. We use the proposed method successfully on several data sets with manifold geometry including an illustrative example of a surface as well as image data. We also show with other experiments that the advantage of the method over the basic SOM is restricted to this specific type of data.

scholarly journals Visible and Near-Infrared Image Acquisition and Fusion for Night Surveillance

Chemosensors ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 75
Author(s):  
Hyuk-Ju Kwon ◽  
Sung-Hak Lee
Keyword(s):  
Image Fusion ◽  
Near Infrared ◽  
Color Space ◽  
Infrared Image ◽  
Human Vision ◽  
Surveillance Systems ◽  
Local Contrast ◽  
Visible Image ◽  
Exposure Fusion ◽  
Multiple Exposures

Image fusion combines images with different information to create a single, information-rich image. The process may either involve synthesizing images using multiple exposures of the same scene, such as exposure fusion, or synthesizing images of different wavelength bands, such as visible and near-infrared (NIR) image fusion. NIR images are frequently used in surveillance systems because they are beyond the narrow perceptual range of human vision. In this paper, we propose an infrared image fusion method that combines high and low intensities for use in surveillance systems under low-light conditions. The proposed method utilizes a depth-weighted radiance map based on intensities and details to enhance local contrast and reduce noise and color distortion. The proposed method involves luminance blending, local tone mapping, and color scaling and correction. Each of these stages is processed in the LAB color space to preserve the color attributes of a visible image. The results confirm that the proposed method outperforms conventional methods.

scholarly journals Analysis of glacier facies using satellite techniques

1991 ◽  
Vol 37 (125) ◽  
pp. 120-128 ◽  
Author(s):  
Richard S. Williams ◽  
Dorothy K. Hall ◽  
Carl S. Benson
Keyword(s):  
Near Infrared ◽  
Infrared Image ◽  
Image Data ◽  
Landsat Data ◽  
Near Infrared Reflectance ◽  
Outlet Glacier ◽  
Northern Margin ◽  
Ice Cap ◽  
Snow Line ◽  
Wet Snow

Abstract The different snow and ice types on a glacier may be subdivided according to the glacier-facies concept. The surficial expression of some facies may be detected at the end of the balance year by the use of visible and near-infrared image data from the Landsat multispectral scanner (MSS) and thematic mapper (TM) sensors. Ice and snow can be distinguished by reflectivity differences in individual or ratioed TM bands on Brúarjökull, an outlet glacier on the northern margin of the Vatnajökull ice cap, Iceland. The Landsat scene shows the upper limit of wet snow on 24 August 1986. Landsat-derived reflectance is lowest for exposed ice and increases markedly at the transient snow line. Above the slush zone is a gradual increase in near-infrared reflectance as a result of decreasing grain-size of the snow, which characterizes drier snow. Landsat data are useful in measuring the areal extent of the ice facies, the slush zone within the wet-snow facies, the snow facies (combined wet-snow, percolation and dry-snow facies), and the respective positions of the transient snow line and the slush limit. In addition, fresh snowfall and/or airborne contaminants, such as soot and tcphra, can limit the utility of Landsat data for delineation of the glacier facies in some cases.

An Improved Biologically-Inspired Image Fusion Method

2018 ◽  
Vol 32 (08) ◽  
pp. 1857004 ◽  
Author(s):  
Yuqing Wang ◽  
Yong Wang
Keyword(s):  
Receptive Field ◽  
Image Fusion ◽  
Color Image ◽  
Infrared Image ◽  
Fusion Method ◽  
Fusion Model ◽  
Biologically Inspired ◽  
Visible Image ◽  
Fusion Methods ◽  
Image Fusion Method

A biologically inspired image fusion mechanism is analyzed in this paper. A pseudo-color image fusion method is proposed based on the improvement of a traditional method. The proposed model describes the fusion process using several abstract definitions which correspond to the detailed behaviors of neurons. Firstly, the infrared image and visible image are respectively ON against enhanced and OFF against enhanced. Secondly, we feed back the enhanced visible images given by the ON-antagonism system to the active cells in the center-surrounding antagonism receptive field. The fused [Formula: see text]VIS[Formula: see text]IR signal are obtained by feeding back the OFF-enhanced infrared image to the corresponding surrounding-depressing neurons. Then we feed back the enhanced visible signal from OFF-antagonism system to the depressing cells in the center-surrounding antagonism receptive field. The ON-enhanced infrared image is taken as the input signal of the corresponding active cells in the neurons, then the cell response of infrared-enhance-visible is produced in the process, it is denoted as [Formula: see text]IR[Formula: see text]VIS. The three kinds of signal are considered as R, G and B components in the output composite image. Finally, some experiments are performed in order to evaluate the performance of the proposed method. The information entropy, average gradient and objective image fusion measure are used to assess the performance of the proposed method objectively. Some traditional digital signal processing-based fusion methods are also evaluated for comparison in the experiments. In this paper, the Quantitative assessment indices show that the proposed fusion model is superior to the classical Waxman’s model, and some of its performance is better than the other image fusion methods.

scholarly journals Defogging Technology Based on Dual-Channel Sensor Information Fusion of Near-Infrared and Visible Light

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Yubin Yuan ◽  
Yu Shen ◽  
Jing Peng ◽  
Lin Wang ◽  
Hongguo Zhang
Keyword(s):  
Visible Light ◽  
Image Fusion ◽  
Near Infrared ◽  
High Efficiency ◽  
Infrared Image ◽  
Low Frequency ◽  
Visible Image ◽  
Primary Color ◽  
Image Defogging ◽  
Channel Image

Since the method to remove fog from images is complicated and detail loss and color distortion could occur to the defogged images, a defogging method based on near-infrared and visible image fusion is put forward in this paper. The algorithm in this paper uses the near-infrared image with rich details as a new data source and adopts the image fusion method to obtain a defog image with rich details and high color recovery. First, the colorful visible image is converted into HSI color space to obtain an intensity channel image, color channel image, and saturation channel image. The intensity channel image is fused with a near-infrared image and defogged, and then it is decomposed by Nonsubsampled Shearlet Transform. The obtained high-frequency coefficient is filtered by preserving the edge with a double exponential edge smoothing filter, while low-frequency antisharpening masking treatment is conducted on the low-frequency coefficient. The new intensity channel image could be obtained based on the fusion rule and by reciprocal transformation. Then, in color treatment of the visible image, the degradation model of the saturation image is established, which estimates the parameters based on the principle of dark primary color to obtain the estimated saturation image. Finally, the new intensity channel image, the estimated saturation image, and the primary color image are reflected to RGB space to obtain the fusion image, which is enhanced by color and sharpness correction. In order to prove the effectiveness of the algorithm, the dense fog image and the thin fog image are compared with the popular single image defogging and multiple image defogging algorithms and the visible light-near infrared fusion defogging algorithm based on deep learning. The experimental results show that the proposed algorithm is better in improving the edge contrast and the visual sharpness of the image than the existing high-efficiency defogging method.

Pencarian File Gambar Berdasarkan Dominasi Warna

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Vina Chovan Epifania ◽  
Eko Sediyono
Keyword(s):  
Digital Image ◽  
Retrieval System ◽  
Color Image ◽  
Color Space ◽  
Image Data ◽  
Image Search ◽  
Test Results ◽  
Application Form ◽  
Space Model ◽  
Image File

Abstract. Image File Searching Based on Color Domination. One characteristic of an image that can be used in image searching process is the composition of the colors. Color is a trait that is easily seen by man in the picture. The use of color as a searching parameter can provide a solution in an easier searching for images stored in computer memory. Color images have RGB values that can be computed and converted into HSL color space model. Use of HSL images model is very easy because it can be calculated using a percent, so that in each pixel of the image can be grouped and named, this can give a dominant values of the colors contained in one image. By obtaining these values, the image search can be done quickly just by using these values to a retrieval system image file. This article discusses the use of the HSL color space model to facilitate the searching for a digital image in the digital image data warehouse. From the test results of the application form, a searching is faster by using the colors specified by the user. Obstacles encountered were still searching with a choice of 15 basic colors available, with a limit of 33% dominance of the color image search was not found. This is due to the dominant color in each image has the most dominant value below 33%.   Keywords: RGB, HSL, image searching Abstrak. Salah satu ciri gambar yang dapat dipergunakan dalam proses pencarian gambar adalah komposisi warna. Warna adalah ciri yang mudah dilihat oleh manusia dalam citra gambar. Penggunaan warna sebagai parameter pencarian dapat memberikan solusi dalam memudahkan pencarian gambar yang tersimpan dalam memori komputer. Warna gambar memiliki nilai RGB yang dapat dihitung dan dikonversi ke dalam model HSL color space. Penggunaan model gambar HSL sangat mudah karena dapat dihitung dengan menggunakan persen, sehingga dalam setiap piksel gambar dapat dikelompokan dan diberi nama, hal ini dapat memberikan suatu nilai dominan dari warna yang terdapat dalam satu gambar. Dengan diperolehnya nilai tersebut, pencarian gambar dapat dilakukan dengan cepat hanya dengan menggunakan nilai tersebut pada sistem pencarian file gambar. Artikel ini membahas tentang penggunaan model HSL color space untuk mempermudah pencarian suatu gambar digital didalam gudang data gambar digital. Dari hasil uji aplikasi yang sudah dibuat, diperoleh pencarian yang lebih cepat dengan menggunakan pilihan warna yang ditentukan sendiri oleh pengguna. Kendala yang masih dijumpai adalah pencarian dengan pilihan 15 warna dasar yang tersedia, dengan batas dominasi warna 33% tidak ditemukan gambar yang dicari. Hal ini disebabkan warna dominan disetiap gambar kebanyakan memiliki nilai dominan di bawah 33%. Kata Kunci: RGB, HSL, pencarian gambar

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