Automatic phytoplankton image smoothing through integrated dual image histogram specification and enhanced background removal method

Abstract

Diatom is a dominant phytoplankton and commonly found in oceans or waterways. The captured phytoplankton microscopic images suffer from low contrast and surrounding debris. These images are not appropriated for identification. Integrated dual image contrast adaptive histogram specification with enhanced background removal (DIHS-BR) is proposed to address these issues by automatically removes the background of the phytoplankton image and improves the image quality while cropping phytoplankton cell. DIHS-BR will automatically remove the background and noises. DIHS-BR consists of two major steps, namely, contrast adaptive histogram specification and background removal by means of edge mask cropping. Results demonstrated that DIHS-BR filtered out the image background and left only the required phytoplankton cell image. Noises are minimized, while the contrast and colour of phytoplankton cells are improved. The average edge-based contrast measure (EBCM) of 83.065 demonstrates the best contrast improvement of the proposed methods compared with the other state-of-the-art methods.

Improving Images in Turbid Water through Enhanced Color Correction and Particle Swarm-Intelligence Fusion (CCPF)

“…However, due to low contrast and haziness in the images, it becomes challenging to distinguish objects from the background. In a different study, Kamarul Baharin et al [21] proposed an image smoothing method specifically for phytoplankton. Their approach involves integrating dual image histogram specification and background removal techniques.…”