Underwater Holographic Sensor for Plankton Studies In Situ including Accompanying Measurements

Abstract

The paper presents an underwater holographic sensor to study marine particles—a miniDHC digital holographic camera, which may be used as part of a hydrobiological probe for accompanying (background) measurements. The results of field measurements of plankton are given and interpreted, their verification is performed. Errors of measurements and classification of plankton particles are estimated. MiniDHC allows measurement of the following set of background data, which is confirmed by field tests: plankton concentration, average size and size dispersion of individuals, particle size distribution, including on major taxa, as well as water turbidity and suspension statistics. Version of constructing measuring systems based on modern carriers of operational oceanography for the purpose of ecological diagnostics of the world ocean using autochthonous plankton are discussed. The results of field measurements of plankton using miniDHC as part of a hydrobiological probe are presented and interpreted, and their verification is carried out. The results of comparing the data on the concentration of individual taxa obtained using miniDHC with the data obtained by the traditional method using plankton catching with a net showed a difference of no more than 23%. The article also contains recommendations for expanding the potential of miniDHC, its purpose indicators, and improving metrological characteristics.

Preliminary results of using the holographic facility to study the ecology of coastal plankton in Lake Baikal

“…The miniDHC digital holographic camera uses DHC technology [13], which allows to obtain focused images of all particles in the investigated volume. Further image processing includes automatic classification of plankton images according to given taxa [13].…”

“…The miniDHC digital holographic camera uses DHC technology [13], which allows to obtain focused images of all particles in the investigated volume. Further image processing includes automatic classification of plankton images according to given taxa [13]. The automatic classification is based on the following taxonomic features: the size of the plankton, the presence of antennae, and the morphological parameter (the ratio of width to length of the plankton image).…”

“…The study was conducted on August 2 and 3, 2021, near the station of the Limnological Institute SB RAS (Irkutsk) in the village of Bolshie Koty (Southern Baikal). The device used in this work, miniDHC, is described in detail in Dyomin V. et al [13]. The measuring equipment was placed at a depth of 5 m, 2.5 m from the bottom and from the surface.…”

Marine Sensors: Recent Advances and Challenges

“…This demonstrated that this energy is sufficient to restore energy used by the battery or the capacitor and continue supplying energy to the sensors. Dyomin et al [ 2 ] developed an underwater holographic sensor to study marine particles, whereas Martins et al [ 3 ] developed and characterized a polyvinylidene difluoride ultrasound transducer to be used as an emitter in underwater wireless communications. In two other articles related to this topic, Nguyen et al [ 4 ] classified underwater sonar images using convolutional neural networks to detect a submerged human body, whereas Sheng et al [ 5 ] proposed a bioinspired twin-inverted multiscale matched filtering method to detect underwater moving targets.…”

Автоматический Выбор Параметров Регистрации Цифровых Голограмм

“…Методы цифровой голографии получили широкое практическое применение при исследовании морских взвешенных частиц, в том числе планктона [1]. Регистрация одной цифровой голограммы и последующая ее численная обработка позволяют получить сфокусированные изображения каждой частицы исследуемого объема [2]. Несмотря на преимущества цифровой голографии в восстановленных изображениях возникают шумы и искажения различного происхождения [3,4] -среднеквадратичное отклонение интенсивности в цифровой голограмме размером .…”