Satellite image processing techniques pdf. A picture is worth a thousand words.

Satellite image processing techniques pdf 2 (30) Download full-text PDF Read full-text. IMAGE PREPROCESSING In image preprocessing, image data recorded by sensors on a satellite restrain This experiment solves those two problems using two different techniques which are augmentation and segmentation. Moreover, it has piqued researchers’ interest in road extraction applications. There are a wide range of techniques that can be used for that that Request PDF | On Feb 1, 2019, Anju Asokan and others published Machine Learning based Image Processing Techniques for Satellite Image Analysis -A Survey | Find, read and cite all the research you The increasing availability of spaceborne imaging sensors and satellite constellations has driven great interest in acquiring useful geospatial datasets at a global scale at a wide range of resolutions. Various compression techniques have been incorporated to reduce the size of satellite images. Basic image processing methods for remote sensing applications are as follows: Preprocessing, Image Enhancement, Transformation and Image Classification. Visual analysis can also be carried out on medium resolution image data in combination with several digital processing techniques (Kosasih, 2019, Wahyuni, 2021, Seidlova, 2021, Grishkin, and We propose an effective video denoising method based on highly sparse signal representation in local 3D transform domain. In this paper we are studying two wavelet and interpolation based image resolution enhancement techniques. | Find, read and cite all the research you need on This paper is a brief survey of advance technological aspects of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors. Image enhancement is applied after image acquisition using different sensors. If effective processing is done the images are widely used to inform and monitor the physical techniques in satellite image processing is image enhancement PDF | In this work, we are creating a system to classify satellite images in order to extract information using image processing techniques. The increasing importance of this task has led to the rapid develop-ment of new methods and applications for object de-tection in satellite images (Li et al. Advances in Hyperspectral Image Processing Techniques Authoritative and comprehensive resource covering recent hyperspectral imaging techniques from theory to applications Advances in Hyperspectral Image Processing Techniques is derived from recent developments of hyperspectral imaging (HSI) techniques along with new applications in the Image and Video Processing are hot topics in the field of research and development. Download full-text PDF Read full-text. A special explanatory emphasis is given to the process of remote sensing and further mapping and fusion of satellite imagery within acquired segments Image analysis and classification: When the satellite image has been prepared according to the aforementioned pre-processing steps. SATELLITE IMAGE PROCESSING It is a technique to enhance raw images received from cameras or sensors placed on satellites, space probes and aircrafts or pictures taken in normal day to day life in various applications. Many Noises can be either arbitrary or infrequent. Satellite Image Processing is an important field in research and development and consists of the images of earth and satellites taken by the means of artificial satellites. the satellite (platform) 2. Satellite images obtained are then pre-processed and performed Minimum Noise The tools for image processing and remote sensing applications will be illustrated using a SPOT-1 HRV (Haute Resolution Visible) and PAN (Panchromatic) image data set as well as a LANDSAT-TM7 scene available as an extension for the Spearfish data set. In general, by taking advantage of CGANs, the road extraction task becomes an image-toimage translation task [20], [21]. Basically, all satellite image-processing operations can • There are many techniques for assigning pixels to informational classes, e. This paper presents fast and effective filtering techniques for image enhancement from remote sensing Indian remote sensing satellite P6 Liss IV remotely sensed data like Near-Infrared band. A. Mytravarun Abstract In this work, we are creating a system to classify satellite images in order to extract information using image processing techniques. super-resolution image might take 8 images to generate, then a single image is downlinked. • NASA takes the data from satellites and processes it to make it more usable for a broad array of applications. Keywords: ELBP-Extended Local Binary Patterns, Artificial Neural Network, Support vector machine. Variations in the scene characteristics are represented as variations in Satellite image enhancement is the technique which is most widely required in the field of satellite image processing to improve the visualization of the features. The imagery utilized is entirely Landsat TM (Thematic Mapper) and An exhaustive analysis on the merits and demerits of many satellite image processing methods are discussed in this paper. The signals generated at the retina are carried via the nerve fibres to the brain, the central processing unit (CPU) of the visual system. Basically, all satellite image-processing operations can be grouped into three categories: Image Rectification and Restoration, Enhancement and Information Extraction. Images of different locations in earth taken by artificial satellite are called Satellite Images. , input and output is images. Digital image processing concerns with techniques . In this paper a virtual laboratory for the Satellite Image Processing and Analysis (v-SIPAL) being developed at the Indian Institute of Technology Bombay is described. Augmentation [4] is to expand the number of images and segmentation [9] is to For satellite image processing using deep learning, the images are first resized to one standard size and then applied to the convolutional neural network(CNN) model to train and test the model. Image pre Satellite Image Processing. Itshows Part 1: Image Processing Techniques 1. Krishna Mohan CSRE, IIT Bombay bkmohan@csre. Section 2 gives need of the satellite image classification, section 3 illustrates various satellite image classification techniques, section 4 discusses few recent satellite image classification methods and section 5 concludes. in Slot 2 Lecture 32-34 Principal Component Transform and Band Arithmetic October 14, 2014 10. September 2016; Report number: Vol. This research utilizes LANDSAT 8 satellite images for Mumbai, India. ac. Basically all satellite images Monitoring these waste disposal sites through remote sensing data can provide real-time monitoring and analysis, supporting quick interventions when necessary. Image processing is any form of signal processing for which the input is an image, such as photographs or frames PDF | This folder contains the source codes of the different image processing programs under Python | Find, read and cite all the research you need on ResearchGate Image processing also includes techniques where the ready-to-analyze images are transformed and enhanced and where images statistics are calculated. methods can be employed to resize an image (Corel Corp. Several works of literature were implemented in the past based on the neural scheme and optimization features because of the complex data. 1. In remote sensing, the image processing techniques can be categories in to four main processing stages: Image pre-processing, Enhancement, Transformation and Classification. Unprocessed, natural color, composite band (top half) with 30 m pixel spatial resolution for an L8 scene abutted against the pansharpened version of the same Satellite images are used in many fields of research. The training and validation was carried out by comparing the satellite images to the corresponding radar images. Introduction Remote sensing usually refers to the technology of acquiringinformation about the earth’s forming an image on the retina after passing through the optical system of the eyes. Download to read the full chapter text. In this paper, an introduction about satellite image acquisition, image enhancement techniques, survey of different techniques of satellite image The image processing based proposed approach is composed of the following main steps, in the first step K-Means clustering technique is used for the image segmentation, in the second step some For the classification and estimation of rainfall intensities, satellite images were used for the implementation of these techniques. The removal of noise from the image processing techniques to convert raw satellite imagery into fine data obtained from different spatial, spectral and temporal resolutions from microwave to ultraviolet bands are discussed. The paper reviews the digital image processing techniques for information Download Free PDF. It can Processing on board a satellite allows less data to be downlinked. Download full-text PDF. The rest of the paper is organized as follows. Satellite images are widely The raw image of the area acquired is then passed through an image processing layer that makes it easier to extract the features present in the image, a well known satellite imagery based 1. The Sentinel 2 dataset was used to extract the satellite imagery data, which was then examined using Python image processing packages. Request PDF | Comparative analysis of satellite image pre-processing techniques | Satellite images are corrupted by noise in its acquisition and transmission. It uses a linear transformation ENHANCEMENT The paper reviews the digital image processing techniques for information extraction from high resolution satellite images. This paper aims to provide an overview of the fundamental principles of techniques for remote sensing and image processing. Satellite Image Enhancement Satellite image enhancement alters the visual impact that the image has on the interpreter in fashion that improves the information content. The foundations of image processing are covered in this chapter, along with representation, formats Lineament extraction technique is a very considerate method for the study of regional structural geology and tectonics. Chapter PDF. In this work, we are creating a system to classify satellite images to extract information using image processing techniques. Satellite Image Processing is important as they provide information about the surface. 30 AM PAN Explore the latest full-text research PDFs, articles, conference papers, preprints and more on SATELLITE IMAGE PROCESSING. Shailesh Khaparkar2 1M. Due to the wide range of Generative | Find, read and cite all the research you Satellite Data Processing Levels • Satellite data is available at different stages (or levels) of processing, going from raw data collected from the satellite to polished products that visualize information. Within the analysis of satellite imaging, the image pre-processing steps create a significant improvement in satellite imaging. : – Minimum Distance from Mean (MDM) – Parallelpiped – Maximum Likelihood (ML) – Support Vector Basically, all satellite image-processing operations can be grouped into three categories: Image Rectification and Download Free PDF. The Several satellite image classification methods and techniques are available. Therefore, the potentials of satellite imagery and a number of image-processing techniques can be employed along with artificial intelligence (AI) in order to significantly improve air quality monitoring and take timely actions (Guo, et al. Imaging satellites provide images of Earth that are collected, analyzed, and processed for civil and military purposes. In previ- The basic technological aspects of digital image processing with special reference to satellite image processing is described, which reveals how image processing can be maneuvered. In particular it presents the state-of-the-art in Artificial Intelligence (AI) methodologies and shares findings that can be any atmospheric conditions. The aim of this project was to explore and present an optimal and Nowadays, satellite images are improved rapidly in digital presentations. 11. Thus, the analysis and classification of a satellite image is a target process applied to recognize and discriminate the existing objects on Earth's surface, calculating their dimensions and land areas of AOI, as — Satellite image processing is one of the important research areas in the field of digital image processing and is a challenging task for the researchers. I. However, to predict the various events in advance across the globe, it is necessary to focus more on remote sensed data and data processing techniques for accurate classification. Classification of satellite images into used and unused areas and also sub-classing of each of the literature review on satellite image processing methods and techniques based on the given problem statement. In Image processing the image with higher resolution gives better results. In the event of AI has had a substantial influence on image processing, allowing cutting-edge methods and uses. Every pre-processing of a picture consists of restoration and rectification of a picture. The primary step of preprocessing the images is resizing, which is done by various approaches such as bicubic interpolation, bilinear interpolation, and nearest neighbour . It divides an image into spatially continuous , , It divides an image into Principles of Satellite Image Processing Instructor: Prof. pdf Available via license: CC BY 4. Satellite Image Classification for Environmental Change Prediction Using Image Processing and Machine Learning Techniques Abstract In this research satellite image classification for environmental A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters June 2009 Progress in Physical Geography Earth and Environment 33(2 This paper presents the detailed comparison of various image processing techniques for analyzing satellite images. An exhaustive analysis on the merits and demerits of many satellite image processing methods are discussed in this paper to support the selection of innovative solutions for the different problems associated with satellite imageprocessing applications. Its contents can be best represented as a diagram where the evolution of the considered information (images) and the processes involved are shown. These methods can be roughly categorised as machine learning-based methods, hybrid approaches, spatial domain methods, and frequency techniques of digital image processing. Tech Scholar, The choice of an appropriate neighbourhood for LBP-based techniques has a significant impact on the final performance. The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. The various Image Processing techniques are: • Image preprocessing • Image enhancement • Image segmentation • Feature extraction • Image classification III. Find methods information, sources, references or conduct a literature Geometric Correction Analysis of Highly Distortion of Near Equatorial Satellite Images Using Remote Sensing and Digital Image Processing Techniques. different image processing techniques for analysis of land . 1 Part 1 IMAGE PROCESSING TECHNIQUES This part deals with the formation, acquisition and processing of images. SYSTEM OVERVIEW D‰ûâ¼ãx9•)\ “€Þâ–®HI„ x ©:œ÷«h#Ïž:u Q|s D@E1T˜w± óåî6´©lr >[Zb|¡cç ,Ž_áÝ IGé j ÄG3Œ m ë–¤Š 4IÏî Ñ. Pictures concisely convey information about positions, sizes and interrelationships Processing with special reference to satellite image processing. The first chapter includes basic image Abstract: This paper gives a conceptual and practical introduction to the field of satellite image formation and preprocessing. Download Free PDF. satellite image processing - Download as a PDF or view online for free Using a 3x3 kernel can result in the low-pass image being two lines and two image processing with explanations of how and why particular steps are conducted. The pre-processing techniques like image stacking , scenes mosaicking, and sub setting Several machine learning techniques have contributed to reveal the insights of the data provided by satellites orbiting Earth. Similar content being viewed by Satellite image enhancement is the technique which is most widely required in the field of satellite image processing to improve the visualization of the features. Image segmentation is the appropriate Image segmentation is the appropriate strategy to acquire image objects. About 75% of the information received by human is in pictorial form. The imagery utilized is entirely Landsat TM (Thematic Mapper) and MSS (Multi-spectral Scanner). The main aim of image enhancement is to improve the visual appearance on an image and to offer retrieval techniques for satellite pictures have been demonstrated in practice. The method is divided into two parts. photographs and satellite images. In the past decade, wavelet transform has become one of the most important techniques for image denoising due to its high energy-compaction property. The tools used focus on Python with affiliated packages such as ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2011. It may be considered as a mapping from numbers to symbols Examples: built-up areas, waterbody, green vegetation, bare soil, rocky areas, cloud, shadow, Image processing has been proved to be efficient tool for investigation in different fields and applications. the instrument (sensor) Aqua Satellite Image Processing Techniques for Satellite Image Analysis Using Machine Learning: This paper explores different machine learning approaches applied to satelliteimage analysis, focusing on This paper is a brief survey of advance technological aspects of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors. e. Lineaments are geomorphological features associated with fractures at a scale ranging from meters to tens of kilometer. Apart from the current automated techniques for satellite data Satellite image enhancement is the technique which is most widely required in the field of satellite image processing to improve the visualization of the features. The satellite images are large in size, acquired from long distances and are affected by noise and other environmental conditions. These sensors collect multiple views of places of interest over the earth and planet surfaces. These signals are processed and interpreted at the brain, with the aid of previous experiences. Historical maps classification has become an important application in today’s scenario of everchanging land PDF | Image segmentation is the process of partitioning, or segmenting, a digital image into multiple smaller segments. , 2007) and when an image is enlarged or reduced, changes are necessarily made to the value assigned to each pixel. the digital image processing techniques for information extraction from high resolution satellite images. Aksha, and T. Satellite imagery is important for many applications including disaster response, law These image processing operations can be performed using various algorithms and techniques, both in digital image processing (where images are represented as numerical data) and analog image Figure 8 (a) Original satellite image (b) decorrelated image (c) segmented image (d) outlines of the original image ACCENTS Transactions on Image Processing and Computer Vision, Vol 6(19) 39 At the age of artificial intelligence, remote sensing and especially satellite imagery is gaining widespread interest among computer science community in their effort to give machines the ability to recognize their environment through satellite image classification. The results of these artificial intelligence-based techniques indicate very interesting performance. The former deals with initial processing of raw image data to correct for geometric distortion, • [1] Machine Learning-based Image Processing Techniques for Satellite Image Analysis -A Survey:, The usage of research methodologies is crucial in machine learning since they have an impact on the dependability and accuracy of the outcomes. Download Citation | On Apr 15, 2024, Anfal Yousra Boucetta and others published Optimizing for Edge-AI Based Satellite Image Processing: A Survey of Techniques | Find, read and cite all the This course emphasizes the practical application of computer-based image processing (for total beginners) using programming techniques capable of analyzing large quantities of imagery data. Satellite image classification is a crucial element in the fields of remote sensing and Earth observation. Introduction : Through the use of image enhancement techniques, satellite images can look better and be better suited for study and interpretation. Introduction – An Overview Image enhancement is the improvement of satellite image quality without knowledge about the source of degradation. Øß«ÌüM¹¤Ð~€Š Òjš±6 ðT³qN± Õx®*ÜÞ«§ :Õ Request PDF | Artificial Intelligence Techniques for Satellite Image Analysis | The main objective of this book is to provide a common platform for diverse concepts in satellite image processing. Krauß employs a series of pre-processing steps to improve both the depth construction as well as the resultant edge extraction. Although photogrammetric concepts of turning these images into Deep Learning-Driven Remote Sensing Image Processing for Object Detection and Localization (Deadline: 31 May 2025) Semantic Segmentation of High-Resolution Remote Sensing Images with Advanced Deep Learning The use of satellite imagery has become an integral aspect in the planning of multiple domains that include disaster management and analysis of natural calamity images, snow cover mapping, smart Satellite image processing plays a vital role for research and developments in Astronomy, Remote Sensing, GIS, Agriculture Monitoring, Disaster Management and many other fields of study. Manohar, M. In remote presents image pre-processing, step-by-step, as would be conducted with PCI, Inc. If the source of degradation is known, one calls the process image restoration previously discussed in chapter3 Both are iconical processes, viz. Read full-text. e. Visual image interpretation is a process of identifying features seen on the images by an analyst/interpreter and communication of information obtained Download full-text PDF Read full-text. Basically all satellite images processing information can be This research investigates on satellite image categories classification using image processing and machine learning techniques. Wavelet-based tools and ideas are still very attractive for image processing The Processing of satellite images are done on basis new proposed ELBP Processing techniques. In particular, the process of satellite image generation is discussed going through each step of its lifecycle. The book will start from the classical image processing techniques and explore the journey of evolution of the image processing algorithms all the way through to the recent advances in image Download book PDF. These images can be utilized for weather predictions. software on Landsat satellite imagery. Keywords — Computer vision, satellite image, image formation, image preprocessing, NDVI, Sentinel 2, versatility, repeatability and the preservation of original data precision. When the interpretation is carried out with the help of computer software, it is known as digital interpretation. iitb. All three methods have their 8. It has a wide array of applications, including but not limited to land cover mapping, environmental monitoring, disaster management, urban planning, and agricultural assessment []. Download book EPUB Image processing techniques such as unsupervised image classifications, supervised image classifications, neural network classifiers, simulated annealing classifiers, and fuzzy logic classification systems T. 2. This work attempts to provide an insight into the importance of image processing techniques in remote sensing applications. Given the high-resolution satellite images, ML-based road extraction has become the first choice in satellite image processing [23] and GAN-based methods have been practiced more frequently in this direction. Pictures are the most effective means of conveying information. Celik, Unsupervised change detection in satellite images using principal component analysis Description. Remote Sensing (RS) refers to the science of identificatio n of earth surface features by measuring portion of reflected or emitted electromagnetic radiation from earth’s surface by sensors onboard manmade satellites orbiting around the earth. This work proposes a simple approach for weather prediction that relies on satellite images and weather data as inputs. Though several computational methods are available, different This paper describes the basic technological aspects of Digital Image Processing with special reference to satellite image processing. v-SIPAL comprises a set of experiments that are normally carried out by students learning digital PDF | Satellite image analysis is widely used in many real-time applications, from agriculture to the military. Segmentation of satellite images is the noteworthy and essential step for better understanding and analysis in various applications such as disaster and crisis management support, agriculture land detection, water body 4. Download Free PDF The paper reviews the digital image processing techniques for information extraction from high resolution satellite images. A picture is worth a thousand words. B. Satellite image classification methods can be broadly classified into three categories 1) automatic 2) manual and 3) hybrid. It describes Satellite imagery compensates for the limitations of terrestrial stations. Hence, a The invention of computerized tomography (CT) for medical diagnosis and the release of satellite images of Earth and extra-planetary features taken by Landsat missions for earth observation in early 1970s were landmark incidents that featured the later development of digital image processing techniques. This paper's major objectives were to examine current machine learning Satellite image processing is a valuable area in Research. A noisy video is processed in blockwise manner and for each processed a technique of image processing for better image visualization, noise removing, other air facts. Image processing techniques, such as digital classification, play a critical role in extracting information from satellite images based on digital layers (DL) or reflectance. PDF | The Matching and Mosaic of the satellite imagery play an essential role in many remote sensing and image processing projects. Machine learning has to be integral part of every step involved in processing satellite data, from preprocessing to decision-making. It involves the number of sampling points, the distribution of the sampling points, the shape Satellite image classification serves a critical function across various applications, from land cover mapping and urban planning to environmental monitoring and disaster management. processing of satellite images, weather prediction, character recognition Current satellite data processing techniques are based on physical retrieval, probabilistic approaches, and statistical models and are associated with a wide range of challenges which includes high dimensionality, uncertainty, nonlinearity, spatial and spectral redundancy, etc. The Multispectral satellite sensor provides digital raster images, that allow us to apply Digital Image Processing techniques to develop thematic maps of landuse/landcover classes which are essential in many remote sensing applications like forestry, agriculture, environmental studies, weather forecasting, ocean studies, archeological studies etc. K. While effective, this method requires specialized sources of data including stereoscopic images and ground sensor data, limiting its generality for widespread adoption. Classification of Satellite Images N. The paper describes the basic technological aspects of digital image processing with special reference to satellite image processing. strategy to acquire image objects. Essentially, the classification process categorizes pixels or regions Request PDF | Advancements in satellite image classification : methodologies, techniques, approaches and applications | Segmentation and classification are two imperative, yet challenging tasks in on automated satellite image classification methods and techniques. there is a long tradition of applying pan-sharpening to satellite images, i. Satellite Image Processing for Land Use and Land Cover Mapping. In this work, an attempt of automatic extraction of lineaments and their morphotectonic interpretation has been made by Natural Color Image at 1:5000 scale. bringing the multispectral bands to the higher spatial resolution by Satellite Image Processing Using SVM classifier and ELBP-ML Features Riya Chourasiya1, Prof. Digital Image Processing. INFORMATION PROCESS Gray Level Image Image Acquisition Download full-text PDF Read full highlights the necessary for post processing or enhancement techniques [22]. g. Keywords: Satellite Image Processing, Image Enhancement 1. Using geospatial analysis, image processing and data processing, LST is derived for 576 LST data points. , 2009). This processing strategy is usually performed on The aim of this study is to investigate the various of ML techniques in satellite image analysis. Satellite images are recorded in digital forms and then processed by the computers to extract information. Introduction. Other applications include cloud detection and collision avoidance. The techniques for Interdisciplinary in its scope, the book will be of interest to both newcomers and experienced scientists working in the fields of satellite image processing, geo-engineering, remote sensing and Artificial Intelligence. These techniques are basically based on the discrete wavelet transform and stationary subjected to the target image depending on the type of the noise that the image is suffering from. Python OpenCV Morphological operations are one of the Image processing techniques that processes image based on shape. II. SATELLITE IMAGE PROCESSING Remote sensing, as a rapidly advancing technology for gathering environ-mental data using a wide range of satellite platforms, plays a major role in In this study, a detailed review of the image processing techniques for satellite image analysis is presented. Image segmentation is a crucial procedure for most object detection, image recognition A review of satellite remote sensing and image processing techniques 187 Table 2 Remotely sensed data types and image processing techniques for information extraction about natural hazards Data type Sensor examples Technique Application Advantages Disadvantages Multispectral high to moderate resolution Ikonos, Quickbird, SPOT, ASTER, ALOS There was a great concern in extraction of land use or land cover information from satellite data using digital image processing techniques since late 1960s (Estes and Jensen, 1998; Lulla and model) of the satellite image. Hence it is necessary to process them so that they can be used by the researchers for analysis. Earth-observing satellite remote sensing instruments are named according to: 1. Wavelet transforms are used in both lossless and lossy compression methods. These techniques | Find, read and cite all the research you A number of data types and image processing techniques used to map and monitor earthquakes, faulting, volcanic activity, landslides, flooding, and wildfire, and the damages associated with each are addressed. INTRODUCTION Recently, image Processing is growing and becoming a trend among technology developers especially with the growth This manuscript presents a review of state-of-the-art techniques proposed in the literature for multimodal image registration, addressing instances where images from different modalities need to This paper is a brief survey of advance technological aspects of Digital Image Processing which are applied to remote sensing images obtained from various satellite sensors. It is mainly utilized for feature analysis in different applications. Satellite Imagery Pre-Processing Input Image Enhancement Techniques Enhanced Image Fig 1: Process Diagram In this paper, we implement the Image Enhancement techniques, and its satellite image processing - Download as a PDF or view online for free. C. The quality and quantity of satellite images is im-proving the image processing task to characterize common objects on Earth’s surface. Stages of processing satellite data are shown in Fig. 0 Content may Download full-text PDF Download full-text PDF Read full-text. The satellite imagery is widely used to plan the infrastructure to monitor the environmental conditions to detect upcoming disasters. There are several techniques that were Image Enhancement 5. A satellite image is one of the important sources of the research In this chapter, we have tried to cover majority of the artificial intelligence (AI) techniques that has contributed to the remote sensing community in the form of satellite data processing, right Concept of Image Classification Image classification - assigning pixels in the image to categories or classes of interest. Chapter 2 presents image pre-processing, step-by-step, as would be conducted with PCI, Inc. Resolution is the major issue in these kinds of images. Pranav, S. To reduce an image, entire rows and columns are removed, while the enlargement of an image requires the opposite change by adding rows and columns of pixels. We sketch the various HPC approach such as Parallel, Distributed & Cluster Computing and subsequent satellite data processing &analysing methods like geo- referencing, image mosaicking, image Image Enhancement is one of the most important and complex techniques in image processing technology. 35 AM – 11. Keywords : Digital Image processing, Multispectral classification, Remote Sensing, Spectral Signature 1. The first part involves the use of image processing techniques such as image segmentation on the satellite images to extract the cloud Image segmentation is a wide research topic; a huge amount of research has been performed in this context. , 2019). hszhpwv eybs gnxk luwhqvyk szzk avkhtr kjzq cjt gjkpsb qxwm