DETECTION AND DISCRIMINATION OF ASTRONOMICAL OBJECTS USING GLOBAL AND LOCAL DETECTION METHODS: CASE OF SLOAN DIGITAL SKY SURVEY (SDSS) IMAGES WITH GRIZ-FILTERS

• Main Author: Ahmad Rizki Jatmiko, Giga
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/38637
• Institution: Institut Teknologi Bandung

Image processing is very important for the advancement of science. With the image, humans can make observations so that science can develop. Therefore, image processing plays a major role in the development of science. One of the sciences that relies heavily on imagery is astronomy. One of the interesting things from the science of astronomical image processing today is how we can detect an object from an image produced from a telescope or a camera lens on a satellite. To process an astronomical image that has been obtained and produce an information from that image, an algorithm is needed. In this research will be shown how the algorithm to detect an object in astronomical images can work even with conditions images that have high noise intensity and various illuminations. The detection of objects in astronomical images will be done using the global detection method and local detection method, then followed by a discriminating step, so that objects that have been detected in these astronomical images can be categorized according to their geometric shapes. The image is obtained from the Sloan Digital Sky Survey (SDSS) using the GRIZ-filter.