Three Dimensional Pulse Coupled Neural Network Based on Hybrid Optimization Algorithm for Oil Pollution Image Segmentation

Abstract

This paper proposes a three dimensional pulse coupled neural network (3DPCNN) image segmentation method based on a hybrid seagull optimization algorithm (HSOA) to solve the oil pollution image. The image of oil pollution is taken by the unmanned aerial vehicle (UAV) in the oil field area. The UAV is good at shooting the ground area, but its ability to identify the oil pollution area is poor. In order to solve this problem, a 3DPCNN-HSOA algorithm is proposed to segment the oil pollution image, and the oil pollution area is segmented to identify the dirty oil area and improve the inspection of environmental pollution. The 3DPCNN image segmentation method has simple structure and good segmentation effect, but it has many parameters and poor segmentation effect for complex oil images. Therefore, we apply HSOA algorithm to optimize the parameters of 3DPCNN algorithm, so as to improve the segmentation accuracy and solve the segmentation of oil pollution images. The experimental results show that the 3DPCNN-HSOA model can separate the oil pollution area from the complex background.

Dynamic Harris Hawks Optimization with Mutation Mechanism for Satellite Image Segmentation

“…In order to further verify the effectiveness of the proposed algorithm in solving practical engineering problems, four oil pollution images are selected for the experiment. These images were taken by the drone in the area of the eighth oil production plant, which can be found in Figure 9 [58]. As can be observed, the oil pollution area of (b) is relatively obvious; while the remaining three images all have strong interference, especially (d).…”

Region Merging Method for Remote Sensing Spectral Image Aided by Inter-Segment and Boundary Homogeneities

“…If the spectral distance between segments are the minimum of each segment, they are selected as a pair of candidates to be merged. (2) Calculate the homogeneity of every initial segment and the global relative homogeneity by Equations (6), (9), and (10). (3) Calculate the homogeneity of adjacent segments and their boundaries by Equations (7) and (8).…”

“…With the rapid development of high resolution remote sensing imaging techniques, geographic object-based image analysis (GEOBIA) has become a promising paradigm to extract accurate and reliable ground information from various detectors [1,2]. GEOBIA framework typically encompasses several sub-procedures such as image segmentation, geo-object recognition, feature extraction and image classification [3][4][5][6][7][8][9]. Image segmentation relies on the spectral or spatial knowledge to produce a spatial partition with contiguous and homogeneous characteristics to form the basis or information carrier for the following processing steps [10,11].…”

A Novel Medical Image Fusion Method Using Multi-Channel Pulse Coupled Neural Networks

“…With the gradual deepening of research on single-and dual-channel PCNN, the method is becoming one of the most popular method in the image fusion. Compared with the wavelet transform [1] that has been applied to multi-focus image fusion, FSD [2] and Gradient pyramid [3], PCNN is still a research focus of multi-focus image fusion, medical image fusion, and the well-known works are [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

“…Firstly, the relevant scholars put forward and summarized the background, principles, further development of the condition and application prospects of PCNN model [4][5][6][7][8][9][10], which laid the foundation for the further development of the model. Then, an adaptive dualchannel pulse-coupled neural network (PCNN) with triplelinking strength (ATD-PCNN) is proposed.…”