Advanced gray-scale morphological filters for the detection of sea mines in side-scan sonar imagery

Author(s):  
Holger Lange ◽  
Luc M. Vincent
2019 ◽  
Vol 11 (11) ◽  
pp. 1281 ◽  
Author(s):  
Xiufen Ye ◽  
Haibo Yang ◽  
Chuanlong Li ◽  
Yunpeng Jia ◽  
Peng Li

When side-scan sonars collect data, sonar energy attenuation, the residual of time varying gain, beam patterns, angular responses, and sonar altitude variations occur, which lead to an uneven gray level in side-scan sonar images. Therefore, gray scale correction is needed before further processing of side-scan sonar images. In this paper, we introduce the causes of gray distortion in side-scan sonar images and the commonly used optical and side-scan sonar gray scale correction methods. As existing methods cannot effectively correct distortion, we propose a simple, yet effective gray scale correction method for side-scan sonar images based on Retinex given the characteristics of side-scan sonar images. Firstly, we smooth the original image and add a constant as an illumination map. Then, we divide the original image by the illumination map to produce the reflection map. Finally, we perform element-wise multiplication between the reflection map and a constant coefficient to produce the final enhanced image. Two different schemes are used to implement our algorithm. For gray scale correction of side-scan sonar images, the proposed method is more effective than the latest similar methods based on the Retinex theory, and the proposed method is faster. Experiments prove the validity of the proposed method.


1993 ◽  
Author(s):  
Qiaofei Wang ◽  
Yrjo A. Neuvo

2019 ◽  
Vol 34 (1) ◽  
Author(s):  
Subarsyah Subarsyah ◽  
Lukman Arifin

Acoustic waves propagate through a medium meet the Snell’s Law, its energy is reflected and some are scattered back at certain angle. The Side Scan Sonar (SSS) methods use this principle to identify seabed character. The intensity of the backscatter greatly depends on the morphology and sediments texture or rocks distributed on seabed.The intensity of backscatter waves is a representation of the morphology, sediments texture, and types of rock that distributed on the seabed, therefore it is possible to estimate sedimentary texture and identify the presence of rocks or coral reefs based on this information. In this publication authors estimate sediments texture, rocks or coral reefs based on backscatter intensity through the image processing on the Side Scan Sonar (SSS) image. Intensity will be converted into pixel values on the image with range value 1-255 (gray scale image) and entropy values which are statistical measures of randomness. Entropy value is maximum when most of pixel value image is in the middle of the colour spectrum range (between very dark to very bright), in contrast, it is minimum when pixel value is in the spectrum of very dark or very bright. Based on both parameters, classification is conducted. The classification is carried out on the SSS image at Bontang and Batam that have very different seabed characters.The classification results using an image processing shows that the distribution of sediment textures consist of 4 (four) classes for either Batam or Bontang. In the Bontang area, very fine sediments were identified which are associated with low value of both intensity and entropy - dark zones in gray scale images, and coarse sediments associated with high value of both intensity and entropy - bright zone in the gray scale image. Similar characteristic is observed in Batam area, which are identified fine sediment (associated to low intensity) - coarse sediments (high intensity). In contrast to Bontang, in Batam the entropy exhibit the opposite value, high value are correlated to fine sediment and vice versa. This might be due to the presence of rocks and sedimentary structures.Keywords: Side Scan Sonar, Intensity, Backscatter and entropy.Gelombang akustik sebagian besar energinya dipantulkan memenuhi prinsip snellius dan sebagian kecil dihamburkan balik dengan sudut. Metode Side Scan Sonar (SSS) memanfaatkan prinsip hambur-balik gelombang untuk mengidentifikasi permukaan dasar laut. Intensitas gelombang dari karakter hambur-balik akan sangat tergantung morfologi dan tekstur sedimen atau batuan dari permukaan dasar lautnya. Intensitas gelombang hambur-balik merupakan representasi dari morfologi, tekstur sedimen, dan jenis batuan yang tersebar di permukaan dasar laut, sehingga sangat memungkinkan untuk melakukan estimasi tekstur sedimen dan identifikasi keberadaan batuan maupun terumbu karang berdasarkan informasi tersebut. Pada publikasi ini akan dilakukan estimasi tekstur sedimen atau batuan berdasarkan intensitas hambur-balik melalui image yang dihasilkan oleh Metode Side Scan Sonar (SSS). Intensitas akan dikonversi ke dalam nilai pixel dalam image dengan rentang nilai 1-255 (gray scale image) dan nilai entropi yang merupakan ukuran statistik ketidakteraturan dari image. Entropi akan maksimum ketika nilai pixel kebanyakan di tengah dari rentang spektrum warna dan sebaliknya akan minimum ketika nilai pixelnya berada di spektrum warna sangat gelap atau sangat terang. Berdasarkan kedua parameter tersebut, kemudian dilakukan klasifikasi. Klasifikasi dilakukan pada data SSS Bontang dan Batam yang memiliki karakter permukaan dasar laut yang sangat berbeda.Hasil klasifikasi dengan image processing memperlihatkan pola sebaran tekstur sedimen masing-masing terdiri dari 4 (empat) kelas baik untuk Batam atau Bontang. Pada area Bontang teridentifikasi sedimen sangat halus yang berasosiasi dengan intensitas dan entropy rendah - zona gelap pada gray scale image dan sedimen kasar yang berasosiasi dengan intensitas dan entropy tinggi - zona terang pada gray scale image. Karakter yang sama juga teramati pada area Batam, yaitu teridentifikasi sedimen halus (berasosiasi dengan intensitas rendah) - sedimen kasar (intensitas tinggi). Namun, berbeda dengan di Bontang, di Batam nilai entropi menunjukkan nilai yang sebaliknya, yaitu nilai tinggi berkorelasi dengan sedimen halus, dan sebaliknya. Hal ini diperkirakan akibat keberadaan batuan dan struktur sedimen.Kata Kunci: Side Scan Sonar, Intensitas, Hambur balik dan Entropi.


Sign in / Sign up

Export Citation Format

Share Document