Visualization of Wave Energy Density Hotspots from EEZ Satellite Images

The energy that may be obtained from the motion of ocean waves is referred to as wave energy in oceans. The collected energy is subsequently put to use for a variety of beneficial tasks, such as the production of electricity, water desalination, and pumping of water. SAR imagery provides information about what is on the ground, but distortions and speckle make these images very different from optical images. Identifying the wave energy density hotspots gives us an advantage of producing more energy with minimum number of wave energy harvesting plants. But nonetheless, it continues to be challenging to capture wave energy for both industrial and commercial usage because of the variability of its geographical and temporal changes. In this paper, SAR images of EEZ region wave data in Pacific Ocean region are taken and processed to visualize the wave power density hotspots. Image processing techniques like canny edge detection is used for edge detection, Fuzzy c means is used for segmentation, K-means clustering is used for clustering the density hotspots, layer masking are used in the process of find the locations of wave energy density hotspots. Then the images are resized into smaller images and the average wave energy density and the coordinates are found for each image. The proposed system is evaluated using performance metrics such as PSNR and MSE are calculated as 10.73 dB and 74.06 dB respectively which proved that the method is accurate and suitable for identifying the density hotspots from the satellite images.