Retrieving Informations from Satellite Images by Detecting and Removing Shadow

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INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY VOLUME 5 ISSUE 1 – MAY 2015 - ISSN: 2349 - 9303

Retrieving Informations from Satellite Images by Detecting and Removing Shadow T.Dhanya Priya1

K.Vidhya2

Sri Ramakrishna Engineering College, dhanyapriya93@gmail.com

Sri Ramakrishna Engineering College, vidhyasrec@gmail.com

Abstract— In accordance with the characteristics of remote sensing images, we put forward a color intensity method of shadow detection and removal. Some approaches for shadow detection and removal use particular color and spectral properties of shadows. In this method, the input satellite image color plane is calculated and the values of RGB are separated. Then the chromaticity is calculated to determine the average value of the segmented region. The Color Intensity algorithm is adopted to remove the shadow and retrieve the corresponding information.

Keywords— chromaticity, color intense algorithm, region of interest, remote sensing, shadow detection, shadow removal. ——————————  —————————— for detection and de-shadowing, respectively. Research on I. INTRODUCTION shadow correction is still an important topic, particularly for urban regions and mountains. Existing shadow detection High resolution satellite image has become an increasingly methods can be roughly categorized into two groups : modelimportant source of information, mainly for applications where based methods and shadow-feature-based methods. The first the need for details is essential as is urban environment. In the group uses prior information such as scene, moving targets, last ten years, with the availability of high-spatial-resolution and camera altitude to construct shadow models. This group of satellites such as IKONOS, QuickBird, GeoEye, and Resource methods is often used in some specific scene conditions such as 3 for the observation of Earth and the rapid development of aerial image analysis and video monitoring. The second group some aerial platforms such as airships and unmanned aerial of methods identifies shadow areas with information such as vehicles, there has been an increasing need to analyze highgray scale, brightness, saturation, and texture. These resolution images for different applications. The Shadow is one approaches for shadow detection and removal use particular of the major problems in remotely sensed imaging which color and spectral properties in shadows. In order to accurately hampers the accuracy of information extraction and change identify a shadow, the threshold value is obtained from the detection. Shadows are caused by the interaction between light estimated grayscale value of the shadow areas. However, and objects, such as buildings, trees and bridges, etc. Shadows information such as scene and camera altitude is not usually can enhance the reality of images, and can often confound readily available. Consequently, most shadow detection algorithms designed to solve other vision tasks such as image algorithms are based on shadow features. For example, the segmentation or the locating and tracking objects in a scene. shadow region appears as a low grayscale value in the image, On the other hand, the poor visibilities of features in shadow and the threshold is chosen between two peaks in the grayscale regions severely degrade the interpretability of the images. histogram of the image data to separate the shadow from the Although shadows can be regarded as a type of useful nonshadow region. In a related study, images are converted information of the 3-D reconstruction, building position into different invariant color spaces (HSV, HCV, YIQ, and recognition, and height estimation, they can also interfere with YCbCr) to obtain shadows. Based on that work, a successive the processing and application of high-resolution remote thresholding scheme was proposed to detect shadows. The sensing images. For example, shadows may cause incorrect method used by Makarau et al accurately detected shadows results during change detection. Consequently, the detection with the blackbody radiation model. Recently, a hierarchical and removal of shadows play an important role in applications supervised classification scheme was used to detect shadows. of high-resolution remote sensing images such as object A variety of image enhancement methods have been classification, object recognition, change detection, and image proposed for shadow removal, such as histogram matching, fusion. In the field of remote sensing, only few works on gamma correction, linear correlation correction(LCC), and shadow detection have been carried out restoration of the color invariance model. In addition, a paired-region-based approach is employed to detect and remove the shadows in a single image by calculating the mainly concerning building detection. In recent years, difference between the shadow and nonshadow regions of thresholding and recovering techniques have become important the same type. Aside from the aforementioned methods,

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