Side scan sonar image data mapping with geographic reference system

Abstract

Many researchers have been done in classifying the surface of the sea floor. Only few concentrated in classifying the sediment layers of the sea floor and the target objects buried. Side Scan Sonar is one such tool, which is used in collecting the images of the seafloor. Sonar equipment transmits a low frequency signal, towards the surface of the seabed for target recognition. It is necessary to locate the area and positioning where the target is located whether it is a ship wreckage or plane crash, mine recognition etc. This paper is proposed to determine the location and position in user friendly matlab software environment, where the sonar image data is collected and is mapped with Global Reference System.

Super resolution enhancement of underwater sonar images

“…The sotware used is matlab. The image acquired is sited in Bay of Bengal [11], latitude 13:07.7935N and longitude 80:18.1166E. Figure 4 illustrates the sonar image data of size 256 × 256 acquired in real time and the resolution enhancement done using techniques The image obtained by sparse representation algorithm gives clear picture and sharp edges.…”

“…Very little research is done on the resolution improvement and is still not resolved in sonar The need for resolution is still emphasised by the real time sonar data collected in XTF format used in our work. The intensities are extracted using matlab software and then converted to image [9][10][11].…”

Optimization of CPBIS methods applied on enhanced fibrin microbeads approach for image segmentation in dynamic databases

“…Gautam and Singhai [2] interpret it as an interdisciplinary endeavor aimed at better equipping experts in the domain of artificial intelligence, processing images, acquisition of images, restoration of images, statistics mining, and gadget gaining knowledge of databases. Kumudham and Rajendran [3] have referred to the large and detailed image databases created as a result of the rapid advancements in image capture and storage systems through which users can obtain useful understanding through image processing. Caponetti et al [4] have conveyed through the article that image mining has become complex due to the existence of massive data of different styles of delay stored within the images.…”