Image Enhancement is a sub area of Image Processing which focuses on processing the images to make the raw image suitable for information extraction as per the desired application. Remote sensing is one such area where satellite image processing is performed for application oriented themes. Remote Sensing helps in acquiring the Earth data from a distant source through space and air borne sensors. These remotely sensed images hold information in varied forms and contains information for different types of applications. Depending upon the nature of application or theme these images are subjected to image enhancement techniques to extract out meaningful information from the available data. Hence it becomes utmost important to enhance the quality of image so as to extract meaningful information from it. Theme specific experts are able to extract the desired features for required application only when the images are able to express the ground feature explicitly. Image enhancement increases the visual perception of the image and experts are able to extract desired information form the image. One of the important feature of the images are edges. Edges represents the local intensity changes. Hence, there has always been an effort to develop effective algorithms to extract edges from images effectively. Various edge detection algorithms are used as a preprocessing step in image processing. Algorithms such as Canny, Canny-Deriche, Sobel, Roberts cross, Prewitt, and Differential are widely used for Edge detection in image processing. Many tools have focused on implementing the edge detection techniques to extract edges effectively but either the tools are proprietary in nature or no proper mechanism is provided to implement them in a standard operational form. A limited number of tools are available in open source domain for satellite image processing. Since remote sensing acquires huge amount of data, with various file formats, not all the tools are capable to process the data effectively. To address this problem, an attempt has been made to develop an edge enhancer tool named Satellite Image Enhancement Toolbox (SIET) on open source software technology. The tool is built using Java (J2SE) with the help of JAI (Java Advance Imaging) Library. The main focus of the tool has been to enhance the quality of image through easy and simple steps. The tool provides facility to apply various Edge detection algorithms such as Sobel, Laplace, Prewitt, Canny and Roberts cross. Along with this, the tool also facilitates sharpening and smoothing of the satellite images. SIET was tested with sample satellite images and the results were found to be satisfactory. SIET has been attempted to implement the edge detection algorithms using the available open source tools and provide a single integrated tool of Image Enhancement, for edge detection with various algorithms. Simple GUI of SIET helps even a novice user to process satellite data easily. The tool is an effort to bring the best out of the current open source technology in satellite image processing so as to benefit the users. The toolbox provides opportunity to the open source community to further enhance the functionality of SIET.

Satellite Image Enhancement Toolbox (SIET) – An open source Image Enhancement Implementation

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