scholarly journals A Survey on Intensification Techniques used in Satellite Images

2021 ◽  
Vol 9 (VII) ◽  
pp. 2242-2245
Author(s):  
Bipin D. Tamkhane
Keyword(s):  
Satellite Images ◽  
Satellite Image ◽  
Research Work ◽  
Research Area ◽  
Research Areas ◽  
Image Intensification ◽  
Human Eyes

An image intensification is a required methodology in field of Satellite image research area. The images taken through satellite are captured from very longer distance and because of this images having garbling and noise as lots of airy barriers are present in between the path. The usage of Satellite images is very diverse in research areas like astrological studies, geographical studies, study of geoscience, etc. Nowadays, after taking a snapshot of an image, some of the radiometric or geometric based enhancement techniques are applied on the images taken from satellite but these techniques do not fulfill the requirements in all application areas. This is what there is a need to improvise the quality of an image before it is being actually used. The main objective behind this research work is to understand the different methodologies used in intensification of satellite images and how can we perform more improvements to existing techniques so these type of images which are taken from satellite are intelligible to the human eyes. The meaning of intensification in term of image is nothing but the altering of a look and feel of the image in a way that the information contained by that image is more readily intelligible visually.

A Comparative Analysis of Existing Satellite Image Enhancement Techniques for Effective Visual Display

2019 ◽  
Vol 16 (9) ◽  
pp. 4003-4007 ◽  
Author(s):  
Neetu Manocha ◽  
Rajeev Gupta
Keyword(s):  
Comparative Analysis ◽  
Image Enhancement ◽  
High Frequency ◽  
Satellite Images ◽  
Satellite Image ◽  
Research Work ◽  
Visual Display ◽  
Image Resolution ◽  
High Image Resolution

Due to environment untidiness and inappropriate setting or dealing of camera, a satellite image contains blur or other types of noises. These images are captured by satellites consist lots of information about the surface of earth or other planets. But, due to blur or noise, the quality of these images is degraded. Now days, there are many fields in which satellite images are used, which effects the environment. The accuracy and effective visual display of satellite images with high image resolution using CBIR technique is major concern. This paper presents a comparative analysis of existing satellite image enhancement techniques to reduce the blur of an image on the basis of accuracy and response time. The aim of research work is to eliminate the noise without losing high frequency details and to enhance the image for effective visual display.

scholarly journals An Investigation on Water Quality of Darlik Dam Drinking Water using Satellite Images

2010 ◽  
Vol 10 ◽  
pp. 1293-1306 ◽  
Author(s):  
Erhan Alparslan ◽  
H. Gonca Coskun ◽  
Ugur Alganci
Keyword(s):  
Water Quality ◽  
Satellite Images ◽  
Satellite Image ◽  
Water Reservoir ◽  
Acquisition Time ◽  
Landsat Tm Image ◽  
Tm Image ◽  
Dissolved Matter ◽  
Image Acquisition Time

Darlik Dam supplies 15% of the water demand of Istanbul Metropolitan City of Turkey. Water quality (WQ) in the Darlik Dam was investigated from Landsat 5 TM satellite images of the years 2004, 2005, and 2006 in order to determine land use/land cover changes in the watershed of the dam that may deteriorate its WQ. The images were geometrically and atmospherically corrected for WQ analysis. Next, an investigation was made by multiple regression analysis between the unitless planetary reflectance values of the first four bands of the June 2005 Landsat TM image of the dam and WQ parameters, such as chlorophyll-a, total dissolved matter, turbidity, total phosphorous, and total nitrogen, measured at satellite image acquisition time at seven stations in the dam. Finally, WQ in the dam was studied from satellite images of the years 2004, 2005, and 2006 by pattern recognition techniques in order to determine possible water pollution in the dam. This study was compared to a previous study done by the authors in the Küçükçekmece water reservoir, also in Istanbul City.

scholarly journals Improved Color Satellite Image Segmentation Using Tsallis Entropy and Granular Computing

2017 ◽  
Vol 6 (4) ◽  
pp. 293
Author(s):  
Jagan Kumar. N ◽  
Agilandeeswari. L ◽  
Prabukumar. M
Keyword(s):  
Satellite Images ◽  
Granular Computing ◽  
Search Algorithm ◽  
Satellite Image ◽  
Research Work ◽  
Cuckoo Search ◽  
Threshold Value ◽  
Computing Methods ◽  
Tsallis Entropy ◽  
Threshold Values

<p>The research work is to improve the segmentation of the color satellite images. In this proposed method the color satellite image can be segmented by using Tsallis entropy and granular computing methods with the help of cuckoo search algorithm. The Tsallis and granular computing methods will used to find the maximum possibility of threshold limits and the cuckoo search will find the optimized threshold values based on threshold limit that is calculated by the Tsallis entropy and granular computing methods and the multilevel thresholding  will used for the segmentation of color satellite images based on the optimized threshold value that will find by this work and these methods will help to select the optimized threshold values for multiple thresholding effectively.<strong></strong></p>

scholarly journals GEOMETRIC QUALITY EVALUATION METHOD FOR MULTI-VIEW SATELLITE IMAGES IN 3D RECONSTRUCTION

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 533-539
Author(s):  
H. Yi ◽  
X. Chen ◽  
D. Wang ◽  
S. Du ◽  
B. Xu ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Satellite Images ◽  
Evaluation Method ◽  
Satellite Image ◽  
Geometric Distortion ◽  
Geometric Quality ◽  
Deviation Coefficient ◽  
Ground Grid ◽  
Straight Lines

Abstract. The quality of the 3D model reconstructed using multi-view satellite image depends on the quality of the image. To evaluate the geometric quality of the satellite image, we proposed a method to evaluate the geometric distortion for satellite images and defined the deviation coefficient as a metric to evaluate the bending degree of a curve. After projecting a ground grid consisting of straight lines into the image space, the geometric distortion of the image can be evaluated quantitatively by calculating the deviation coefficients of the projection trajectories. Experiments have been carried out with three datasets obtained by JiLin-1, GaoFen-2, and WorldView-3 respectively. The results show that the proposed method can used to evaluate the geometric quality of satellite images effectively, and this evaluation method will be useful in image selecting in 3D reconstruction using multi-view satellite images.

scholarly journals Compression of High-Resolution Satellite Images Using Optical Image Processing

2021 ◽  
Author(s):  
Anirban Patra ◽  
Arijit Saha ◽  
Debasish Chakraborty ◽  
Kallol Bhattacharya
Keyword(s):  
High Resolution ◽  
Satellite Communication ◽  
Satellite Image ◽  
Research Work ◽  
Storage Space ◽  
Optical Image Processing ◽  
High Resolution Satellite Images ◽  
Fixed Orientation ◽  
Novel Method

This chapter presents a novel method for compressing satellite imagery using phase grating to facilitate the optimization of storage space and bandwidth in satellite communication. In this research work, each Satellite image is first modulated with high grating frequency in a fixed orientation. Due to this modulation, three spots (spectrum) have been generated. From these three spots, by applying Inverse Fourier Transform in any one band, we can recover the image. Out of these three spots, one is center spectrum spot and other spots represent two sidebands. Care should be taken during the spot selection is to avoid aliasing effect. At the receiving end, to recover image we use only one spectrum. We have proved that size of the extracted image is less than the original image. In this way, compression of satellite image has been performed. To measure quality of the output images, PSNR value has been calculated and compared this value with previous techniques. As high-resolution satellite image contains a lot of information, therefore to get detail information from extracted image, compression ratio should be as minimum as possible.

Vector Quantization for Satellite Image Compression

2016 ◽  
Vol 5 ◽  
pp. 22
Author(s):  
Sanjith Sathya Joseph ◽  
R. Ganesan
Keyword(s):  
Image Compression ◽  
Vector Quantization ◽  
Satellite Images ◽  
Signal To Noise Ratio ◽  
Satellite Image ◽  
Signal To Noise ◽  
Transmission Process ◽  
Noise Ratio ◽  
Time Required

Image compression is the process of reducing the size of a file without humiliating the quality of the image to an unacceptable level by Human Visual System. The reduction in file size allows as to store more data in less memory and speed up the transmission process in low bandwidth also, in case of satellite images it reduces the time required for the image to reach the ground station. In order to increase the transmission process compression plays an important role in remote sensing images.  This paper presents a coding scheme for satellite images using Vector Quantization. And it is a well-known technique for signal compression, and it is also the generalization of the scalar quantization.  The given satellite image is compressed using VCDemo software by creating codebooks for vector quantization and the quality of the compressed and decompressed image is compared by the Mean Square Error, Signal to Noise Ratio, Peak Signal to Noise Ratio values.

scholarly journals Modified Local and Global Contrast Enhancement Algorithm for Color Satellite Image

2019 ◽  
Vol 224 ◽  
pp. 04010
Author(s):  
Viacheslav Voronin
Keyword(s):  
Image Processing ◽  
Image Enhancement ◽  
Satellite Images ◽  
Color Image ◽  
State Of The Art ◽  
Satellite Image ◽  
Detailed Model ◽  
Global Contrast ◽  
Enhancement Algorithm

The quality of remotely sensed satellite images depends on the reflected electromagnetic radiation from the earth’s surface features. Lack of consistent and similar amounts of energy reflected by different features from the earth’s surface results in a poor contrast satellite image. Image enhancement is the image processing of improving the quality that the results are more suitable for display or further image analysis. In this paper, we present a detailed model for color image enhancement using the quaternion framework. We introduce a novel quaternionic frequency enhancement algorithm that can combine the color channels and the local and global image processing. The basic idea is to apply the α-rooting image enhancement approach for different image blocks. For this purpose, we split image in moving windows on disjoint blocks. The parameter alfa for every block and the weights for every local and global enhanced image driven through optimization of measure of enhancement (EMEC). Some presented experimental results illustrate the performance of the proposed approach on color satellite images in comparison with the state-of-the-art methods.

scholarly journals Discussion of different Remote sensing satellite possibilities for scientifical Earth observations

2021 ◽  
Vol 264 ◽  
pp. 04007
Author(s):  
Aybek Arifjanov ◽  
Shamshodbek Akmalov ◽  
Shakhzod Shodiev ◽  
Abdukarim Haitov
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Water Discharge ◽  
Satellite Image ◽  
Research Area ◽  
Daily Monitoring ◽  
Medium Resolution ◽  
Very High Spatial Resolution ◽  
High Resolution Images ◽  
Very High

More than 1,000 satellites are launched into space, and they differ in their functions, rotation orbits, resolution, and other properties. Scientists divide the satellites into low-resolution, medium-resolution, high-resolution, and very high-resolution satellites by their properties. Now, the biggest challenge facing scientists is to use some of these different resolution images in their field. To get the expected result, it is very important to analyze the image that needs an which gives more accurate results. Therefore, the main attention of this article is aimed to find the answer to these problems. In this article 3 satellite images which have different resolution are analyzed. The possibility of middle-resolution images of MODIS, high-resolution images of Landsat, and very high-resolution images of WorldView-2 (WV-2) satellites using GIS are analyzed. A research area was the Syrdarya region, and downloaded different images of satellites of this area and compared with using e Cognition. According to the results, a more accurate satellite image for irrigation sets information is WorldView-2 images. In comparison analysis, it shows more accurate properties than other satellite images. As irrigation sets are small objects for the analysis, very high spatial resolution satellite images are important. Water discharge and surface change happen very fast; thus, it requires daily monitoring of the condition. And in this case, the temporal resolution of the MODIS and Landsat is 16 day, and it is a too long period.

scholarly journals Sampling strategy of an epidemiological survey using a satellite image program

2019 ◽  
Vol 53 ◽  
pp. 47 ◽  
Author(s):  
Ticiane De Góes Mário Ferreira ◽  
José Mariano Da Rocha ◽  
Silvia Cardoso de David ◽  
Jociana Boligon ◽  
Maísa Casarin ◽  
...  
Keyword(s):  
Life Stress ◽  
Skin Color ◽  
Satellite Images ◽  
Periodontal Diseases ◽  
Satellite Image ◽  
Sampling Strategy ◽  
Epidemiological Survey ◽  
Clinical Approach ◽  
Color Data

OBJECTIVE: To describe the sampling strategy of an epidemiological survey with the aid of satellite images, including details of the multistage probability sampling process. METHODS: A probability sample of individuals living in the rural area of Rosário do Sul, state of Rio Grande do Sul, Brazil, aged 15 years old or more, was evaluated. Participants answered questionnaires (medical history, sociodemographic characteristics, habits, alcohol use, quality of life, stress, rumination, and self-perceived periodontal diseases), and were subjected to clinical oral examinations as well as anthropometric measurements (blood pressure, height, weight, abdominal and waist circumferences). Oral evaluation comprehended a complete periodontal exam at six sites per tooth, including the following assessments: furcation involvement; dental abrasion; tooth decay, including the indexing of missing and filled surfaces; O’Brien index; gingival abrasion; oral cavity and lip lesions; complete periapical radiographic exam, and use of prostheses. Besides this oral clinical approach, subgingival plaque, crevicular gingival fluid, saliva, and blood samples were collected. Examiners were trained and calibrated during previous evaluations. A pilot study allowed the logistic of the performed exams to be adjusted as needed. RESULTS: Among 1,087 eligible individuals, 688 were examined (63.3%). Age, sex, and skin color data were compared to data from the last demographic census (2010) of the Brazilian Institute of Geography and Statistics, which served to validate the sampling strategy. CONCLUSIONS: The careful methods used in this study, in which satellite images were used in the delimitation of epidemiological areas, ensure the quality of the estimates obtained and allow for these estimates to be used in oral health surveillance and health policies improvements.

scholarly journals Promising Modern Research Areas in Smart Mobility

2020 ◽  
Vol 18 (3) ◽  
pp. 44-52
Author(s):  
V. N. Tregubov
Keyword(s):  
Web Of Science ◽  
Research Area ◽  
Urban Transport ◽  
Urban Mobility ◽  
Planning Decisions ◽  
Research Areas ◽  
Automated Processing ◽  
Smart Mobility ◽  
Promising Development

Contemporary smart mobility technology makes it possible to solve the problems of urban transport, improving quality of urban mobility, increasing availability of transport, and ensuring its efficiency. The objective of the study is to identify key trends of research on smart mobility in recent scientific sources. The author, using VOS Viewer program, carried out a bibliometric analysis of publications indexed in the Web of Science and Scopus databases and containing keywords related to smart urban mobility. Co-citations, cross-references, shared keywords, co-authorships have been analyzed for the entire set of selected publications. As a result, a map of links between publications in the field of smart mobility was built, defining existing relationships between keywords and authors in this area. Also, a map of clusters was built , which displays proximity of publications to each other. A cluster comprises a group of research closely related via research topics, authors, and keywords. Clustering of publications was conducted followed by identifying six clusters, each of which reflects single promising research area in the field of smart mobility. The results obtained make it possible to identify promising development trends for smart mobility through automated processing of a highquality array of publications. The results can be used by municipal officials, transportation business and academia to review and analyze emerging smart mobility technologies and to make informed urban transport planning decisions.

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